memory+component

SUBJECT AREA: Automotive engineering, Land transport

[br]

[br]

[br]

Royce was the younger son of a flour miller. His father's death forced him to earn his own living from the age of 10 selling newspapers, as a post office messenger boy, and in other jobs. At the age of 14, he became an apprentice at the Great Northern Railway's locomotive works, but was unable to complete his apprenticeship due to a shortage of money. He moved to a tool company in Leeds, then in 1882 he became a tester for the London Electric Light \& Power Company and attended classes at the City \& Guilds Technical College. In the same year, the company made him Chief Electrical Engineer for the lighting of the streets of Liverpool.

In 1884, at the age of 21, he founded F.H. Royce \& Co (later called Royce Ltd, from 1894 to 1933) with a capital of £70, manufacturing arc lamps, dynamos and electric cranes. In 1903, he bought a 10 hp Deauville car which proved noisy and unreliable; he therefore designed his own car. By the end of 1903 he had produced a twocylinder engine which ran for many hundreds of hours driving dynamos; on 31 March 1904, a 10 hp Royce car was driven smoothly and silently from the works in Cooke Street, Manchester. This car so impressed Charles S. Rolls, whose London firm were agents for high-class continental cars, that he agreed to take the entire output from the Manchester works. In 1906 they jointly formed Rolls-Royce Ltd and at the end of that year Royce produced the first 40/50 hp Silver Ghost, which remained in production until 1925 when it was replaced by the Phantom and Wraith. The demand for the cars grew so great that in 1908 manufacture was transferred to a new factory in Derby.

In 1911 Royce had a breakdown due to overwork and his lack of attention to taking regular meals. From that time he never returned to the works but continued in charge of design from a drawing office in his home in the south of France and later at West Wittering, Sussex, England. During the First World War he designed the Falcon, Hawk and Condor engines as well as the VI2 Eagle, all of which were liquid-cooled. Later he designed the 36.7-litre Rolls-Royce R engines for the Vickers Supermarine S.6 and S.6B seaplanes which were entered for the Schneider Trophy (which they won in 1929 and 1931, the 5.5 having won in 1927 with a Napier Lion engine) and set a world speed record of 408 mph (657 km/h) in 1931; the 1941 Griffon engine was derived from the R.

Royce was an improver rather than an innovator, though he did invent a silent form of valve gear, a friction-damped slipper flywheel, the Royce carburettor and a spring drive for timing gears. He was a modest man with a remarkable memory who concentrated on perfecting the detail of every component. He married Minnie Punt, but they had no children. A bust of him at the Derby factory is captioned simply "Henry Royce, Mechanic".

[br]

χάρις, ιτος, ἡ (Hom.+) acc. quite predom. χάριν, but χάριτα Ac 24:27; 25:9 v.l.; Jd 4 and pl. χάριτας Ac 24:27 v.l.; 1 Cl 23:1 (Eur., Hel. 1378; Hdt. 6, 41; X., Hell. 3, 5, 16; ins, pap; Zech 4:7; 6:14; EpArist 272, pl. 230.—B-D-F §47, 3; W-S. §9, 7; Mayser 271f; Thackeray 150; Helbing 40f; Mlt-H. 132.—It seems that χάρις is not always clearly differentiated in mng. fr. χαρά; Apollodorus [II B.C.]: 244 Fgm. 90 Jac. says in the second book περὶ θεῶν: κληθῆναι δὲ αὐτὰς ἀπὸ μὲν τ. χαρᾶς Χάριτας• καὶ γὰρ πολλάκις … οἱ ποιηταὶ τ. χάριν χαρὰν καλοῦσιν ‘the [deities] Charites are so called from χαρά [joy], for poets freq. equate χάρις with χαρά’. Cp. the wordplay AcPl Ha 8, 7 χαρᾶς καὶ χάριτος the house was filled with gaiety and gratitude.).

① a winning quality or attractiveness that invites a favorable reaction, graciousness, attractiveness, charm, winsomeness (Hom.+; Jos., Ant. 2, 231) of human form and appearance παῖς λίαν εὐειδής ἐν χάριτι an exceptionally fine-looking and winsome youth AcPl Ha 3, 13. Of speech (Demosth. 51, 9; Ps.-Demetr. [I A.D.], Eloc. §127; 133; 135 al.; Eccl 10:12; Sir 21:16; Jos., Ant. 18, 208) οἱ λόγοι τῆς χάριτος (gen. of quality) the gracious words Lk 4:22. ὁ λόγος ὑμῶν πάντοτε ἐν χάριτι let your conversation always be winsome Col 4:6 (cp. Plut., Mor. 514f; s. also HAlmqvist, Plut. u. das NT ’46, 121f; Epict. 3, 22, 90). τὸ πρόσωπον αὐτοῦ χάριτος ἐπληροῦτο MPol 12:1 can also be placed here in case χάρις means nothing more than graciousness (s. 4 below); prob. also GJs 7:3 (s. 3b).

② a beneficent disposition toward someone, favor, grace, gracious care/help, goodwill (almost a t.t. in the reciprocity-oriented world dominated by Hellenic influence [cp. e.g. OGI 669, 29] as well as by the Semitic sense of social obligation expressed in the term חֶסֶד [NGlueck, Das Wort ḥesed in alttestamentlichen Sprachgebrauche etc. 1927]. Of a different order and spirit is the subset of reciprocity known as Roman patronage, in which superiority of the donor over the client is clearly maintained)

ⓐ act., that which one grants to another, the action of one who volunteers to do someth. not otherwise obligatory χάρις θεοῦ ἦν ἐπʼ αὐτό Lk 2:40. ἡ χάρις τοῦ θεοῦ (cp. τῇ τοῦ θεοῦ Κλαυδίου χάριτι OGI 669, 29) Ac 11:2 D; 14:26. τοῦ κυρίου 15:40.—Esp. of the beneficent intention of God (cp. χ. in reference to God: Apollon. Rhod. 3, 1005 σοὶ θεόθεν χάρις ἔσσεται; Dio Chrys. 80 [30], 40 χ. τῶν θεῶν; Ael. Aristid. 13 p. 320 D.; 53 p. 620; Sextus 436b; likew. in LXX, Philo, Joseph.; SibOr 4, 46=189; 5, 330; Ezk. Trag. 162 [Eus., PE 9, 29, 12].—χ. to denote beneficent dispensations of the emperor: OGI 669, 44 [I A.D.]; BGU 19 I, 21 [II A.D.] χάρ. τοῦ θεοῦ Αὐτοκράτορος; 1085 II, 4) and of Christ, who give (undeserved) gifts to people; God: δικαιούμενοι δωρεὰν τῇ αὐτοῦ χάριτι Ro 3:24. Cp. 5:15a, 20f; 6:1; 11:5 (ἐκλογή 1), 6abc; Gal 1:15 (διά A 3e); Eph 1:6f (KKuhn, NTS 7, ’61, 337 [reff. to Qumran lit.]); 2:5, 7, 8; cp. Pol 1:3; 2 Th 1:12; 2:16; 2 Ti 1:9; Tit 2:11 (ἡ χάρ. τοῦ θεοῦ σωτήριος; s. Dibelius, Hdb. exc. after Tit 2:14); 3:7; Hb 2:9 (χωρίς 2aα); 4:16a (DdeSilva, JBL 115, ’96, 100–103); 1 Cl 50:3; ISm 9:2; IPol 7:3. ἐν χάρ[ιτι θεοῦ] AcPl Ha 7, 23 (restoration uncertain). κατὰ χάριν as a favor, out of goodwill (cp. Pla., Leg. 740c; schol. on Soph., Oed. Col. 1751 p. 468 Papag.) Ro 4:4 (opp. κατὰ ὀφείλημα), 16.—The beneficence or favor of Christ: διὰ τῆς χάριτος τοῦ κυρίου Ἰησοῦ πιστεύομεν σωθῆναι Ac 15:11. Cp. Ro 5:15b; 2 Cor 8:9; 1 Ti 1:14; IPhld 8:1. On Ac 2:47 in this sense s. TAnderson, NTS 34, ’88, 604–10.

ⓑ pass., that which one experiences fr. another (Arrian, Anab. Alex. 3, 26, 4) χάριν ἔχειν have favor 3J 4 v.l. πρός τινα with someone=win his respect Ac 2:47 (cp. 2a end; cp. Pind., O. 7, 89f χάριν καὶ ποτʼ ἀστῶν καὶ ποτὶ ξείνων grant him respect in the presence of his townfolk as well as strangers); παρά τινι (Appian, Bell. Civ. 2, 89 §376) Hm 10, 3, 1, cp. 5, 1, 5. εὑρεῖν χάριν παρά τινι (Philo, Leg. All. 3, 77, end) Lk 1:30; Hs 5, 2, 10; ἐνώπιόν τινος Ac 7:46; GJs 11:2 (JosAs 15:14). ἐν τοῖς μέλλουσι μετανοεῖν among those who are about to repent Hm 12, 3, 3. Ἰησοῦς προέκοπτεν χάριτι παρὰ θεῷ καὶ ἀνθρώποις Lk 2:52 (an indication of exceptional ἀρετή, cp. Pind. above). Cp. Ac 4:33; 7:10 (ἐναντίον Φαραώ); Hb 4:16b.—ποία ὑμῖν χάρις ἐστίν; what credit is that to you? Lk 6:32–34; s. D 1:3; 2 Cl 13:4. Cp. 1 Cor 9:16 v.l. In these passages the mng. comes close to reward (s. Wetter [5 below] 209ff w. reff.).—Also by metonymy that which brings someone (God’s) favor or wins a favorable response fr. God 1 Pt 2:19, 20.

ⓒ In Christian epistolary lit. fr. the time of Paul χάρις is found w. the sense (divine) favor in fixed formulas at the beginning and end of letters (Zahn on Gal 1:3; vDobschütz on 1 Th 1:1; ELohmeyer, ZNW 26, 1927, 158ff; APujol, De Salutat. Apost. ‘Gratia vobis et pax’: Verb. Dom. 12, ’32, 38–40; 76–82; WFoerster, TW II ’34, 409ff; Goodsp., Probs. 141f. S. also the lit. s.v. χαίρω 2b). At the beginning of a letter χάρις ὑμῖν καὶ εἰρήνη (sc. εἴη; New Docs 8, 127f) Ro 1:7; 1 Cor 1:3; 2 Cor 1:2; Gal 1:3; Eph 1:2; Phil 1:2; Col 1:2; 1 Th 1:1; 2 Th 1:2; Phlm 3; Rv 1:4; without ὑμῖν Tit 1:4. χάρις ὑμῖν καὶ εἰρήνη πληθυνθείη 1 Pt 1:2; 2 Pt 1:2; 1 Cl ins. χάρις, ἔλεος, εἰρήνη 1 Ti 1:2; 2 Ti 1:2; 2J 3 (on the triplet cp. En 5:7 φῶς καὶ χάρις καὶ εἰρήνη).—At the end ἡ χάρις (τοῦ κυρίου ἡμῶν Ἰησοῦ Χριστοῦ etc.) μεθʼ ὑμῶν (or μετὰ πάντων ὑμῶν etc.) Ro 16:20, 23 (24) v.l.; 1 Cor 16:23; 2 Cor 13:13; Gal 6:18; Eph 6:24; Phil 4:23; Col 4:18; 1 Th 5:28; 2 Th 3:18; 1 Ti 6:21; 2 Ti 4:22; Tit 3:15; Phlm 25; Hb 13:25; Rv 22:21; 1 Cl 65:2. ἔσται ἡ χάρις μετὰ πάντων τῶν φοβουμένων τὸν Κύριον GJs 25:2. ὁ κύριος τῆς δόξης καὶ πάσης χάριτος μετὰ τοῦ πνεύματος ὑμῶν B 21:9. χάρις ὑμῖν, ἔλεος, εἰρήνη, ὑπομονὴ διὰ παντός ISm 12:2. ἔρρωσθε ἐν χάριτι θεοῦ 13:2.

③ practical application of goodwill, (a sign of) favor, gracious deed/gift, benefaction

ⓐ on the part of humans (X., Symp. 8, 36, Ages. 4, 3; Appian, Bell. Civ. 1, 49 §213; Dionys. Hal. 2, 15, 4) χάριν (-ιτα) καταθέσθαι τινί (κατατίθημι 2) Ac 24:27; 25:9. αἰτεῖσθαι χάριν 25:3 (in these passages from Ac χ. suggests [political] favor, someth. one does for another within a reciprocity system. Cp. Appian, Bell. Civ. 1, 108 §506 ἐς χάριν Σύλλα=as a favor to Sulla; ApcSed 8:1 οὐκ ἐποίησάς μοι χάριν=you did me no favor). ἵνα δευτέραν χάριν σχῆτε that you might have a second proof of my goodwill 2 Cor 1:15 (unless χάρις here means delight [so in poetry, Pind. et al., but also Pla., Isocr.; L-S-J-M s.v. χάρις IV; cp. also the quot. fr. Apollodorus at the beg. of the present entry, and the fact that χαρά is v.l. in 2 Cor 1:15]; in that case δευτέρα means double; but s. comm.). Of the collection for Jerusalem (cp. Appian, Bell. Civ. 3, 42 §173 χάριτας λαμβάνειν=receive gifts) 1 Cor 16:3; 2 Cor 8:4, 6f, 19 (DdeSilva, JBL 115, ’96, 101). Cp. B 21:7.—Eph 4:29 may suggest a demonstration of human favor (cp. Plut., Mor. 514e χάριν παρασκευάζοντες ἀλλήλοις), but a ref. to the means by which divine grace is mediated is not to be ruled out (s. b below).

ⓑ on the part of God and Christ; the context will show whether the emphasis is upon the possession of divine favor as a source of blessings for the believer, or upon a store of favor that is dispensed, or a favored status (i.e. standing in God’s favor) that is brought about, or a gracious deed wrought by God in Christ, or a gracious work that grows fr. more to more (so in contrast to the old covenant Mel., P. 3, 16 al.). God is called ὁ θεὸς πάσης χάριτος 1 Pt 5:10, i.e. God, who is noted for any conceivable benefit or favor; cp. B 21:9.—χάριν διδόναι τινί show favor to someone (Anacr. 110 Diehl; Appian, Ital. 5 §10): τὸν δόντα αὐτῷ τὴν χάριν GJs 14:2. ταπεινοῖς δίδωσι χάριν (Pr 3:34) Js 4:6b; 1 Pt 5:5; 1 Cl 30:2; without a dat. Js 4:6a (Menand., Epitr. 231 S. [55 Kö.]). Perh. καὶ ἔβαλλε κύριος … χάριν ἐπʼ αὐτήν GJs 7:3 (but s. 1 above). The Logos is πλήρης χάριτος J 1:14. Those who belong to him receive of the fullness of his grace, χάριν ἀντὶ χάριτος vs. 16 (ἀντί 2). Cp. vs. 17. τὴν χάριν ταύτην ἐν ᾗ ἑστήκαμεν this favor (of God) we now enjoy Ro 5:2 (Goodsp.).—5:17; 1 Cor 1:4; 2 Cor 4:15 (divine beneficence in conversion); cp. Ac 11:23; 6:1; Gal 1:6 (by Christ’s gracious deed); 2:21; 5:4; Col 1:6; 2 Ti 2:1; Hb 12:15; 13:9; 1 Pt 1:10, 13; 3:7 (συνκληρονόμοι χάριτος ζωῆς fellow-heirs of the gift that spells life; s. ζωή 2bα); 5:12; 2 Pt 3:18; Jd 4; IPhld 11:1; ISm 6:2. Christians stand ὑπὸ χάριν under God’s gracious will as expressed in their release from legal constraint Ro 6:14f, or they come ὑπὸ τὸν ζυγὸν τῆς χάριτος αὐτοῦ 1 Cl 16:17 (ζυγός 1). The proclamation of salvation is the message of divine beneficence τὸ εὐαγγέλιον τῆς χάριτος τοῦ θεοῦ Ac 20:24 or ὁ λόγος τῆς χάριτος αὐτοῦ (=τοῦ κυρίου) 14:3; 20:32. Even the gospel message can be called ἡ χάρις τοῦ θεοῦ 13:43; cp. 18:27; MPol 2:3. τὸ πνεῦμα τῆς χάριτος the Spirit from or through whom (God’s) favor is shown Hb 10:29 (AArgyle, Grace and the Covenant: ET 60, ’48/49, 26f).—Pl. benefits, favors (Diod S 3, 2, 4; 3, 73, 6; Sb 8139, 4 [ins of I B.C.] of Isis; Jos., C. Ap. 2, 190) 1 Cl 23:1.—Nelson Glueck, Das Wort ḥesed etc. 1927, but s. FAndersen, ‘Yahweh, the Kind and Sensitive God’: God Who is Rich in Mercy, ed. PO’Brien/DPeterson ’86.

④ exceptional effect produced by generosity, favor. Of effects produced by divine beneficence which go beyond those associated with a specific Christian’s status (ins μεγάλαι χάριτες τοῦ θεου: FCumont, Syria 7, 1926, 347ff), in the congregations of Macedonia 2 Cor 8:1 and Corinth 9:14; cp. vs. 8; in Rome AcPl Ha 7, 8. The Christian confessor is in full possession of divine grace ISm 11:1. Paul knows that through the χάρις of God he has been called to be an apostle, and that he has been fitted out w. the powers and capabilities requisite for this office fr. the same source: Ro 1:5; 12:3; 15:15; 1 Cor 3:10; 15:10ab (for the subject matter cp. Polyb. 12, 12b, 3 αὐτὸν [Alex. the Great] ὑπὸ τοῦ δαιμονίου τετευχέναι τούτων ὧν ἔτυχεν=whatever he has received he has received from what is divine. [For this reason he does not deserve any divine honors.]); 2 Cor 12:9; Gal 2:9; Eph 3:2, 7f; Phil 1:7.—The χάρις of God manifests itself in various χαρίσματα: Ro 12:6; Eph 4:7; 1 Pt 4:10. This brings into view a number of passages in which χάρις is evidently to be understood in a very concrete sense. It is hardly to be differentiated fr. δύναμις (θεοῦ) or fr. γνῶσις or δόξα (q.v. 1b. On this subj. s. Wetter [5 below] p. 94ff; esp. 130ff; pap in the GLumbroso Festschr. 1925, 212ff: χάρις, δύναμις, πνεῦμα w. essentially the same mng.; PGM 4, 2438; 3165; Herm. Wr. 1, 32; Just., D. 87, 5 ἀπὸ χάριτος τῆς δυνάμεως τοῦ πνεύματος). οὐκ ἐν σοφίᾳ σαρκικῇ ἀλλʼ ἐν χάριτι θεοῦ 2 Cor 1:12. οὐκ ἐγὼ δὲ ἀλλὰ ἡ χάρις τοῦ θεοῦ σὺν ἐμοί 1 Cor 15:10c. αὐξάνετε ἐν χάριτι καὶ γνώσει τοῦ κυρίου 2 Pt 3:18; cp. 1 Cl 55:3; B 1:2 (τῆς δωρεᾶς πνευματικῆς χάρις). Stephen is said to be πλήρης χάριτος καὶ δυνάμεως Ac 6:8. Divine power fills the Christian confessor or martyr w. a radiant glow MPol 12:1 (but s. 1 above). As the typical quality of the age to come, contrasted w. the κόσμος D 10:6.

⑤ response to generosity or beneficence, thanks, gratitude (a fundamental component in the Gr-Rom. reciprocity system; exx. fr. later times: Diod S 11, 71, 4 [χάριτες=proofs of gratitude]; Appian, Syr. 3, 12; 13. Cp. Wetter [below] p. 206f) χάριν ἔχειν τινί be grateful to someone (Eur., Hec. 767; X., An. 2, 5, 14; Pla., Phlb. 54d; Ath. 2, 1; PLips 104, 14 [I B.C.] χάριν σοι ἔχω) foll. by ὅτι (Epict. 3, 5, 10; Jos., C. Ap. 1, 270; 2, 49) Lk 17:9 (ERiggenbach, NKZ 34, 1923, 439–43); mostly of gratitude to God or Christ; χάρις in our lit. as a whole, in the sense gratitude, refers to appropriate respone to the Deity for benefits conferred (Hom., Pind., Thu. et al.; ins, pap, LXX; Jos., Ant. 7, 208) χάριν ἔχω τῷ θεῷ (POxy 113, 13 [II A.D.] χάριν ἔχω θεοῖς πᾶσιν.—Epict. 4, 7, 9) 2 Ti 1:3; foll. by ὅτι because 1 Ti 1:12 (Herm. Wr. 6, 4 κἀγὼ χάριν ἔχω τῷ θεῷ …, ὅτι; Jos., Ant. 4, 316); χάριν ἔχειν ἐπί τινι be grateful for someth. Phlm 7 v.l. (to humans). ἔχωμεν χάριν let us be thankful (to God) Hb 12:28 (the reason for it is given by the preceding ptc. παραλαμβάνοντες). Elliptically (B-D-F §128, 6; cp. Rob. 1201f) χάρις (ἔστω) τῷ θεῷ (X., Oec. 8, 16 πολλὴ χάρις τοῖς θεοῖς; Epict. 4, 4, 7 χάρις τῷ θεῳ; BGU 843, 6 [I/II A.D.] χάρις τοῖς θεοῖς al. in pap since III B.C..—Philo, Rer. Div. Her. 309) Ro 7:25; MPol 3:1. Foll. by ὅτι (X., An. 3, 3, 14 τοῖς θεοῖς χάρις ὅτι; PFay 124, 16 τοῖς θεοῖς ἐστιν χάρις ὅτι; Epict. 4, 5, 9) Ro 6:17. Foll. by ἐπί τινι for someth. (UPZ 108, 30 [99 B.C.]) 2 Cor 9:15. The reason for the thanks is given in the ptc. agreeing w. τῷ θεῷ 2:14; 8:16; 1 Cor 15:57 (cp. Jos., Ant. 6, 145; Philo, Somn. 2, 213). Thankfulness (Appian, Bell. Civ. 3, 15 §51 πρός τινα=toward someone) χάριτι in thankfulness 10:30. So prob. also ἐν τῇ χάριτι in a thankful spirit Col 3:16 (Dibelius, Hdb. ad loc.). πλησθῆναι χαρᾶς καὶ χάριτος AcPl Ha 8, 7. S. εὐχαριστέω, end. Also PSchubert, Form and Function of the Pauline Thanksgivings ’39.—OLoew, Χάρις, diss., Marburg 1908; GWetter, Charis 1913; AvHarnack, Sanftmut, Huld u. Demut in der alten Kirche: JKaftan Festschr. 1920, 113ff; NBonwetsch, Zur Geschichte des Begriffs Gnade in der alten Kirche: Harnack Festgabe 1921, 93–101; EBurton, Gal ICC 1921, 423f; WWhitley, The Doctrine of Grace ’32; JMoffatt, Grace in the NT ’31; RWinkler, D. Gnade im NT: ZST 10, ’33, 642–80; RHomann, D. Gnade in d. Syn. Ev.: ibid. 328–48; JWobbe, D. Charisgedanke b. Pls ’32; RBultmann, Theologie des NT ’48, 283–310 (Paul); HBoers, Ἀγάπη and Χάρις in Paul’s Thought: CBQ 59, ’97, 693–713; on 2 Cor 8: FDanker, Augsburg Comm. 2 Cor, 116–34; PRousselot, La Grâce d’après St. Jean et d’après St. Paul: SR 18, 1928, 87–108, Christent. u. Wissensch. 8, ’32, 402–30; JMontgomery, Hebrew Hesed and Gk. Charis: HTR 32, ’39, 97–102; Dodd 61f; TTorrance, The Doctrine of Grace in the Apost. Fathers, ’48; JRenié, Studia Anselmiana 27f, ’51, 340–50; CRSmith, The Bible Doctrine of Grace, ’56; EFlack, The Concept of Grace in Bibl. Thought: Bibl. Studies in Memory of HAlleman, ed. Myers, ’60, 137–54; DDoughty, NTS 19, ’73, 163–80.—B. 1166. DELG. M-M. EDNT. TW. Spicq. Sv.

   1) Programs and the Complexity of Human Mental Processes

   In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)

   2) Artificial Intelligence Is an Engineering Discipline

   Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)

   3) A Sceptical View of Artificial Intelligence

   Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....

   When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)

   4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, Eventually

   Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)

   5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the Program

   Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)

   6) The Meaning of a Symbolic Description

   What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)

   7) The Principle of Artificial Intelligence

   [AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)

   8) Artificial Intelligence Recognizes the Need for Knowledge in Its Systems

   The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)

   9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract Form

   The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)

    10) There Are Many Types of Reasoning

   There are many different kinds of reasoning one might imagine:

    Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."

    Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)

    11) Programs Are Beginning to Do Things That Critics Have Asserted to Be Impossible

   Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)

    12) The Synthesis of Man and Machine

   Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)

    13) The Thesis of Good Old-Fashioned Artificial Intelligence (GOFAI)

   The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)

    14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory Formation

   It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)

    15) Four Kinds of Artificial Intelligence

   We might distinguish among four kinds of AI.

   ♦ Nonpsychological AI

   Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.

   ♦ Weak Psychological AI

   Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.

   ♦ Strong Psychological AI

... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)

   ♦ Suprapsychological AI

   Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)

    16) Determination of Relevance of Rules in Particular Contexts

   Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)

    17) Form and Content Are Not Fundamentally Different

   Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)

    18) The Assumption That the Mind Is a Formal System

   Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)

    19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence

   The primary goal of Artificial Intelligence is to make machines smarter.

   The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)

    20) Mathematical Logic Provides the Basis for Theory in AI

   The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....

   AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)

    21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions

   In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)

    22) Definitions of Artificial Intelligence

   Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)

    23) The Computer Can Not Be a Model of the Mind

   Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)

    24) Computers Will Not Always Be Inferior to Human Brains

   The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)

   1) All Human Complex Problem Solving Is Creativity

   Put in this bald way, these aims sound utopian. How utopian they areor rather, how imminent their realization-depends on how broadly or narrowly we interpret the term "creative." If we are willing to regard all human complex problem solving as creative, then-as we will point out-successful programs for problem solving mechanisms that simulate human problem solvers already exist, and a number of their general characteristics are known. If we reserve the term "creative" for activities like discovery of the special theory of relativity or the composition of Beethoven's Seventh Symphony, then no example of a creative mechanism exists at the present time. (Simon, 1979, pp. 144-145)

   2) Artificial Intelligence Models of Creative Association

   Among the questions that can now be given preliminary answers in computational terms are the following: how can ideas from very different sources be spontaneously thought of together? how can two ideas be merged to produce a new structure, which shows the influence of both ancestor ideas without being a mere "cut-and-paste" combination? how can the mind be "primed," so that one will more easily notice serendipitous ideas? why may someone notice-and remember-something fairly uninteresting, if it occurs in an interesting context? how can a brief phrase conjure up an entire melody from memory? and how can we accept two ideas as similar ("love" and "prove" as rhyming, for instance) in respect of a feature not identical in both? The features of connectionist AI models that suggest answers to these questions are their powers of pattern completion, graceful degradation, sensitization, multiple constraint satisfaction, and "best-fit" equilibration.... Here, the important point is that the unconscious, "insightful," associative aspects of creativity can be explained-in outline, at least-by AI methods. (Boden, 1996, p. 273)

   3) Creative Innovation and Social Independence

   There thus appears to be an underlying similarity in the process involved in creative innovation and social independence, with common traits and postures required for expression of both behaviors. The difference is one of product-literary, musical, artistic, theoretical products on the one hand, opinions on the other-rather than one of process. In both instances the individual must believe that his perceptions are meaningful and valid and be willing to rely upon his own interpretations. He must trust himself sufficiently that even when persons express opinions counter to his own he can proceed on the basis of his own perceptions and convictions. (Coopersmith, 1967, p. 58)

   4) Ego Strength and Emotional Stability among Creative Geniuses

   he average level of ego strength and emotional stability is noticeably higher among creative geniuses than among the general population, though it is possibly lower than among men of comparable intelligence and education who go into administrative and similar positions. High anxiety and excitability appear common (e.g. Priestley, Darwin, Kepler) but full-blown neurosis is quite rare. (Cattell & Butcher, 1970, p. 315)

   5) Its Mundane Character

   he insight that is supposed to be required for such work as discovery turns out to be synonymous with the familiar process of recognition; and other terms commonly used in the discussion of creative work-such terms as "judgment," "creativity," or even "genius"-appear to be wholly dispensable or to be definable, as insight is, in terms of mundane and well-understood concepts. (Simon, 1989, p. 376)

   6) Mozart's Musical Ideas Came to Him in Polished Form

   From the sketch material still in existence, from the condition of the fragments, and from the autographs themselves we can draw definite conclusions about Mozart's creative process. To invent musical ideas he did not need any stimulation; they came to his mind "ready-made" and in polished form. In contrast to Beethoven, who made numerous attempts at shaping his musical ideas until he found the definitive formulation of a theme, Mozart's first inspiration has the stamp of finality. Any Mozart theme has completeness and unity; as a phenomenon it is a Gestalt. (Herzmann, 1964, p. 28)

   7) Scientific Theories and Works of Art Alike Originate in Fantasy

   Great artists enlarge the limits of one's perception. Looking at the world through the eyes of Rembrandt or Tolstoy makes one able to perceive aspects of truth about the world which one could not have achieved without their aid. Freud believed that science was adaptive because it facilitated mastery of the external world; but was it not the case that many scientific theories, like works of art, also originated in phantasy? Certainly, reading accounts of scientific discovery by men of the calibre of Einstein compelled me to conclude that phantasy was not merely escapist, but a way of reaching new insights concerning the nature of reality. Scientific hypotheses require proof; works of art do not. Both are concerned with creating order, with making sense out of the world and our experience of it. (Storr, 1993, p. xii)

   8) Self- Esteem and Creative Expression

   The importance of self-esteem for creative expression appears to be almost beyond disproof. Without a high regard for himself the individual who is working in the frontiers of his field cannot trust himself to discriminate between the trivial and the significant. Without trust in his own powers the person seeking improved solutions or alternative theories has no basis for distinguishing the significant and profound innovation from the one that is merely different.... An essential component of the creative process, whether it be analysis, synthesis, or the development of a new perspective or more comprehensive theory, is the conviction that one's judgment in interpreting the events is to be trusted. (Coopersmith, 1967, p. 59)

   9) Stages in Creative Problem- Solving

   In the daily stream of thought these four different stages [preparation; incubation; illumination or inspiration; and verification] constantly overlap each other as we explore different problems. An economist reading a Blue Book, a physiologist watching an experiment, or a business man going through his morning's letters, may at the same time be "incubating" on a problem which he proposed to himself a few days ago, be accumulating knowledge in "preparation" for a second problem, and be "verifying" his conclusions to a third problem. Even in exploring the same problem, the mind may be unconsciously incubating on one aspect of it, while it is consciously employed in preparing for or verifying another aspect. (Wallas, 1926, p. 81)

    10) The Bisociative Pattern of the Creative Synthesis

   he basic, bisociative pattern of the creative synthesis [is] the sudden interlocking of two previously unrelated skills, or matrices of thought. (Koestler, 1964, p. 121)

    11) The Earliest Stages in the Creative Process Involve a Commerce with Disorder

   Even to the creator himself, the earliest effort may seem to involve a commerce with disorder. For the creative order, which is an extension of life, is not an elaboration of the established, but a movement beyond the established, or at least a reorganization of it and often of elements not included in it. The first need is therefore to transcend the old order. Before any new order can be defined, the absolute power of the established, the hold upon us of what we know and are, must be broken. New life comes always from outside our world, as we commonly conceive that world. This is the reason why, in order to invent, one must yield to the indeterminate within him, or, more precisely, to certain illdefined impulses which seem to be of the very texture of the ungoverned fullness which John Livingston Lowes calls "the surging chaos of the unexpressed." (Ghiselin, 1985, p. 4)

    12) The Inner Life of the Creative Process

   New life comes always from outside our world, as we commonly conceive our world. This is the reason why, in order to invent, one must yield to the indeterminate within him, or, more precisely, to certain illdefined impulses which seem to be of the very texture of the ungoverned fullness which John Livingston Lowes calls "the surging chaos of the unexpressed." Chaos and disorder are perhaps the wrong terms for that indeterminate fullness and activity of the inner life. For it is organic, dynamic, full of tension and tendency. What is absent from it, except in the decisive act of creation, is determination, fixity, and commitment to one resolution or another of the whole complex of its tensions. (Ghiselin, 1952, p. 13)

    13) The Problem of What Impels the Creative Person

   [P]sychoanalysts have principally been concerned with the content of creative products, and with explaining content in terms of the artist's infantile past. They have paid less attention to examining why the artist chooses his particular activity to express, abreact or sublimate his emotions. In short, they have not made much distinction between art and neurosis; and, since the former is one of the blessings of mankind, whereas the latter is one of the curses, it seems a pity that they should not be better differentiated....

   Psychoanalysis, being fundamentally concerned with drive and motive, might have been expected to throw more light upon what impels the creative person that in fact it has. (Storr, 1993, pp. xvii, 3)

    14) Theories of Creative Thinking

   A number of theoretical approaches were considered. Associative theory, as developed by Mednick (1962), gained some empirical support from the apparent validity of the Remote Associates Test, which was constructed on the basis of the theory.... Koestler's (1964) bisociative theory allows more complexity to mental organization than Mednick's associative theory, and postulates "associative contexts" or "frames of reference." He proposed that normal, non-creative, thought proceeds within particular contexts or frames and that the creative act involves linking together previously unconnected frames.... Simonton (1988) has developed associative notions further and explored the mathematical consequences of chance permutation of ideas....

   Like Koestler, Gruber (1980; Gruber and Davis, 1988) has based his analysis on case studies. He has focused especially on Darwin's development of the theory of evolution. Using piagetian notions, such as assimilation and accommodation, Gruber shows how Darwin's system of ideas changed very slowly over a period of many years. "Moments of insight," in Gruber's analysis, were the culminations of slow long-term processes.... Finally, the information-processing approach, as represented by Simon (1966) and Langley et al. (1987), was considered.... [Simon] points out the importance of good problem representations, both to ensure search is in an appropriate problem space and to aid in developing heuristic evaluations of possible research directions.... The work of Langley et al. (1987) demonstrates how such search processes, realized in computer programs, can indeed discover many basic laws of science from tables of raw data.... Boden (1990a, 1994) has stressed the importance of restructuring the problem space in creative work to develop new genres and paradigms in the arts and sciences. (Gilhooly, 1996, pp. 243-244; emphasis in original)

   1) Grammar as Analogous to a Scientific Theory

   I think that the failure to offer a precise account of the notion "grammar" is not just a superficial defect in linguistic theory that can be remedied by adding one more definition. It seems to me that until this notion is clarified, no part of linguistic theory can achieve anything like a satisfactory development.... I have been discussing a grammar of a particular language here as analogous to a particular scientific theory, dealing with its subject matter (the set of sentences of this language) much as embryology or physics deals with its subject matter. (Chomsky, 1964, p. 213)

   2) Native Speakers and Their Grammar

   Obviously, every speaker of a language has mastered and internalized a generative grammar that expresses his knowledge of his language. This is not to say that he is aware of the rules of grammar or even that he can become aware of them, or that his statements about his intuitive knowledge of his language are necessarily accurate. (Chomsky, 1965, p. 8)

   3) The Reduction of Transformation Rules In a Science of Grammar

   Much effort has been devoted to showing that the class of possible transformations can be substantially reduced without loss of descriptive power through the discovery of quite general conditions that all such rules and the representations they operate on and form must meet.... [The] transformational rules, at least for a substantial core grammar, can be reduced to the single rule, "Move alpha" (that is, "move any category anywhere"). (Mehler, Walker & Garrett, 1982, p. 21)

   4) The Relationship of Transformational Grammar to Semantics and to Human Performance

   he implications of assuming a semantic memory for what we might call "generative psycholinguistics" are: that dichotomous judgments of semantic well-formedness versus anomaly are not essential or inherent to language performance; that the transformational component of a grammar is the part most relevant to performance models; that a generative grammar's role should be viewed as restricted to language production, whereas sentence understanding should be treated as a problem of extracting a cognitive representation of a text's message; that until some theoretical notion of cognitive representation is incorporated into linguistic conceptions, they are unlikely to provide either powerful language-processing programs or psychologically relevant theories.

   Although these implications conflict with the way others have viewed the relationship of transformational grammars to semantics and to human performance, they do not eliminate the importance of such grammars to psychologists, an importance stressed in, and indeed largely created by, the work of Chomsky. It is precisely because of a growing interdependence between such linguistic theory and psychological performance models that their relationship needs to be clarified. (Quillian, 1968, p. 260)

   5) The Terminologies of Formal Grammar

   here are some terminological distinctions that are crucial to explain, or else confusions can easily arise. In the formal study of grammar, a language is defined as a set of sentences, possibly infinite, where each sentence is a string of symbols or words. One can think of each sentence as having several representations linked together: one for its sound pattern, one for its meaning, one for the string of words constituting it, possibly others for other data structures such as the "surface structure" and "deep structure" that are held to mediate the mapping between sound and meaning. Because no finite system can store an infinite number of sentences, and because humans in particular are clearly not pullstring dolls that emit sentences from a finite stored list, one must explain human language abilities by imputing to them a grammar, which in the technical sense is a finite rule system, or programme, or circuit design, capable of generating and recognizing the sentences of a particular language. This "mental grammar" or "psychogrammar" is the neural system that allows us to speak and understand the possible word sequences of our native tongue. A grammar for a specific language is obviously acquired by a human during childhood, but there must be neural circuitry that actually carries out the acquisition process in the child, and this circuitry may be called the language faculty or language acquisition device. An important part of the language faculty is universal grammar, an implementation of a set of principles or constraints that govern the possible form of any human grammar. (Pinker, 1996, p. 263)

   6) The Theory of Grammar

   A grammar of language L is essentially a theory of L. Any scientific theory is based on a finite number of observations, and it seeks to relate the observed phenomena and to predict new phenomena by constructing general laws in terms of hypothetical constructs.... Similarly a grammar of English is based on a finite corpus of utterances (observations), and it will contain certain grammatical rules (laws) stated in terms of the particular phonemes, phrases, etc., of English (hypothetical constructs). These rules express structural relations among the sentences of the corpus and the infinite number of sentences generated by the grammar beyond the corpus (predictions). (Chomsky, 1957, p. 49)