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Cognitive architecture

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1494: 254:, decentralized approach; bio-inspired techniques often involve the method of specifying a set of simple generic rules or a set of simple nodes, from the interaction of which emerges the overall behavior. It is hoped to build up complexity until the end result is something markedly complex (see complex systems). However, it is also arguable that systems designed 1482: 770:, which uses groups of these neurons to complete cognitive tasks via flexibile coordination. Components of the model communicate using spiking neurons that implement neural representations called "semantic pointers" using various firing patterns. Semantic pointers can be understood as being elements of a compressed neural vector space. 126:
One can distinguish between the theory of cognition and the implementation of the theory. The theory of cognition outlined the structure of the various parts of the mind and made commitments to the use of rules, associative networks, and other aspects. The cognitive architecture implements the theory
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Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg,
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hypothesis about the fixed structures that provide a mind, whether in natural or artificial systems, and how they work together — in conjunction with knowledge and skills embodied within the architecture — to yield intelligent behavior in a diversity of complex
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provided a theory of human associative memory. He included more aspects of his research on long-term memory and thinking processes into this research and eventually designed a cognitive architecture he eventually called
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a connectionist distributed neural architecture for simulated creatures or robots, where modules of neural networks composed of heterogenous neurons (including receptors and effectors) can be designed and evolved.
119:'s use of the term "cognitive architecture". Anderson's lab used the term to refer to the ACT theory as embodied in a collection of papers and designs. (There was not a complete implementation of ACT at the time.) 1131:
Vernon, David; Metta, Giorgio; Sandini, Giulio (April 2007). "A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computational Agents".
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Schmidhuber, Jürgen; Kavukcuoglu, Koray; Silver, David; Graves, Alex; Antonoglou, Ioannis; Wierstra, Daan; Riedmiller, Martin (2015). "Deep learning in neural networks: An overview".
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on computers. The software used to implement the cognitive architectures was also called "cognitive architectures". Thus, a cognitive architecture can also refer to a blueprint for
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Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Graves, Alex; Antonoglou, Ioannis; Wierstra, Daan; Riedmiller, Martin (2013). "Playing Atari with Deep Reinforcement Learning".
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on the basis of observations of what humans and other animals can do, rather than on observations of brain mechanisms, are also biologically inspired, though in a different way.
658:. HTM is a method for discovering and inferring the high-level causes of observed input patterns and sequences, thus building an increasingly complex model of the world. 92:
provided a possible "architecture for cognition" because it included some commitments for how more than one fundamental aspect of the human mind worked (in EPAM's case,
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Eliasmith, C.; Stewart, T. C.; Choo, X.; Bekolay, T.; DeWolf, T.; Tang, Y.; Rasmussen, D. (29 November 2012). "A Large-Scale Model of the Functioning Brain".
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Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Graves, Alex; Antonoglou, Ioannis; Wierstra, Daan; Riedmiller, Martin (2014). "Neural Turing Machines".
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as a realizable architecture that could store large patterns and retrieve them based on partial matches with patterns representing current sensory inputs.
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is a reference model architecture that provides a theoretical foundation for designing, engineering, integrating intelligent systems software for
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multi-agent system that adds a cognitive architecture to the agents for eliciting more realistic (human-like) behaviors in virtual environments.
143:. The term 'architecture' implies an approach that attempts to model not only behavior, but also structural properties of the modelled system. 992: 489: 1498: 1111: 332: 300: 103: 66: 962: 449: 1027: 907: 1486: 475: 412: 402: 192: 1514: 521: 380: 372: 247: 208: 168: 39: 987: 703: 582: 775: 681: 255: 251: 172: 55: 615: 135:
processes that act like certain cognitive systems. Most often, these processes are based on human cognition, but other
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in a similar fashion to humans and a neural network that may be able to access an external memory like a conventional
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and serve as the frameworks for useful artificial intelligence programs. Successful cognitive architectures include
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The Cerebellar Model Articulation Controller (CMAC) is a type of neural network based on a model of the mammalian
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assumptions, relying only on emergent properties of processing units (e.g., nodes ). Hybrid architectures such as
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and to a computational instantiation of such a theory used in the fields of artificial intelligence (AI) and
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Newell, Allen. 1990. Unified Theories of Cognition. Harvard University Press, Cambridge, Massachusetts.
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Shane; Hassabis, Demis (25 February 2015). "Human-level control through deep reinforcement learning".
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This Week's Citation Classic: Anderson J R & Bower G H. Human associative memory. Washington
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Albus, James S. (August 1979). "Mechanisms of planning and problem solving in the brain".
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Extended Artificial Memory. Toward an integral cognitive theory of memory and technology
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combine both types of processing. A further distinction is whether the architecture is
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is programmed in a top-down fashion. Although such a system may be designed to
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systems may also be suitable. Cognitive architectures form a subset of general
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started research on human memory in the early 1970s and his 1973 thesis with
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In 1983 John R. Anderson published the seminal work in this area, entitled
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tasks, generalization, and pattern recognition with changeable attention.
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of the human brain. The underlying algorithm is based on a combination of
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Mobile robots XVII: 26–28 October 2004, Philadelphia, Pennsylvania, USA
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https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19920002425.pdf
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by Chris Eliasmith at the Centre for Theoretical Neuroscience at the
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Some well-known cognitive architectures, in alphabetical order:
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This architecture is part of the family of correlation-based
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Denning, Peter J. "Sparse distributed memory." (1989).Url:
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Flexible Attention-based Cognitive Architecture for Robots
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of Numenta, Inc. that models some of the structural and
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can be used to further refine comprehensive theories of
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Spaun (Semantic Pointer Architecture Unified Network)
34:refers to both a theory about the structure of the 1348:"DeepMind's Nature Paper and Earlier Related Work" 603:. Holographs have been shown to be effective for 1188:(Thesis). Technical University of Kaiserslautern 1022:. London, UK: Routledge, Taylor & Francis. 1133:IEEE Transactions on Evolutionary Computation 893:Biologically inspired cognitive architectures 766:– Spaun is a network of 2,500,000 artificial 54:(Adaptive Control of Thought – Rational) and 8: 860:(though it could be argued whether they are 718:'Procedural Reasoning System', developed by 708:Michael S. Gashler, University of Arkansas. 407:the cognitive architecture, developed under 1055:. Institute for Creative Technologies. 2024 268: 115:. He and his students were influenced by 1374: 1279: 1258: 444:in 1975 and has been extensively used in 1010: 490:University of California in Los Angeles 69:defines a cognitive architecture as a " 648:theory of brain function described by 1020:Cognitive Design for Artificial Minds 7: 301:4D-RCS Reference Model Architecture 67:Institute for Creative Technologies 1102:," in: CC. Nr. 52 Dec 24–31, 1979. 963:Neural correlates of consciousness 250:, on the other hand, takes a more 25: 908:Cognitive architecture comparison 520:developed by Susan L. Epstein at 488:developed by Erik Mueller at the 1492: 1480: 413:Rensselaer Polytechnic Institute 27:Blueprint for intelligent agents 522:The City University of New York 373:University of Technology Sydney 248:Biologically-inspired computing 209:parallel distributed processing 199:, with a neural correlate of a 169:Information Processing Language 151:Cognitive architectures can be 40:computational cognitive science 988:Never-Ending Language Learning 704:MANIC (Cognitive Architecture) 583:Holographic associative memory 124:The Architecture of Cognition. 1: 1165:Douglas Whitney Gage (2004). 1117:The Architecture of Cognition 371:and Benjamin Johnston at the 1385:10.1016/j.neunet.2014.09.003 1240:10.1016/0025-5564(79)90063-4 616:Hierarchical temporal memory 415:and University of Missouri. 215:, a prime example being the 983:Unified theory of cognition 573:on earlier related work in 569:. (Also see an overview by 395:University of Hertfordshire 177:unified theory of cognition 131:. It proposes (artificial) 1531: 790:Carnegie Mellon University 672:inspired extension to the 545:The company has created a 448:and also as for automated 341:Extended Artificial Memory 329:Carnegie Mellon University 289:Carnegie Mellon University 852:Subsumption architectures 844:NASA Ames Research Center 834:Sparse distributed memory 742:Otto-Friedrich University 393:and Peter C. Lane at the 1228:Mathematical Biosciences 1179:Dr. Lars Ludwig (2013). 1145:10.1109/TEVC.2006.890274 1053:"Cognitive Architecture" 968:Pandemonium architecture 883:Artificial consciousness 620:This architecture is an 567:recurrent neural network 549:that learns how to play 504:New Bulgarian University 315:unmanned ground vehicles 1436:10.1126/science.1225266 1206:Novianto, Rony (2014). 1075:"The Feigenbaum Papers" 1018:Lieto, Antonio (2021). 688:Global Workspace Theory 622:online machine learning 227:, or (more concretely) 18:Cognitive architectures 1515:Cognitive architecture 1499:Cognitive architecture 1497:Quotations related to 1487:Cognitive architecture 998:Open Mind Common Sense 794:University of Michigan 764:University of Waterloo 595:. It was inspired by 492:under Michael G. Dyer 446:reinforcement learning 32:cognitive architecture 928:Computer architecture 923:Commonsense reasoning 696:University of Memphis 597:holonomic brain model 1489:at Wikimedia Commons 589:associative memories 1428:2012Sci...338.1202E 1422:(6111): 1202–1205. 1318:10.1038/nature14236 1310:2015Natur.518..529M 1079:Stanford University 913:Cognitive computing 819:The Emotion Machine 644:model based on the 624:model developed by 438:robotic controllers 295:and Sashank Varma. 270: 141:agent architectures 42:. These formalized 898:Blue Brain Project 856:developed e.g. by 722:and Amy Lansky at 690:, developed under 636:properties of the 571:Jürgen Schmidhuber 476:Indiana University 468:Douglas Hofstadter 429:. It is a type of 369:Mary-Anne Williams 269: 129:intelligent agents 1485:Media related to 1304:(7540): 529–533. 978:Social simulation 973:Simulated reality 918:Cognitive science 868: 867: 724:SRI International 646:memory-prediction 559:short-term memory 502:developed at the 391:Brunel University 347:TU Kaiserslautern 211:in mid-1980s and 16:(Redirected from 1522: 1496: 1484: 1468: 1462: 1456: 1455: 1411: 1405: 1404: 1378: 1358: 1352: 1351: 1344: 1338: 1337: 1292: 1286: 1285: 1283: 1271: 1265: 1264: 1262: 1250: 1244: 1243: 1234:(3–4): 247–293. 1223: 1217: 1216: 1214: 1203: 1197: 1196: 1194: 1193: 1187: 1176: 1170: 1163: 1157: 1156: 1128: 1122: 1112:John R. Anderson 1109: 1103: 1096: 1090: 1089: 1087: 1085: 1071: 1065: 1064: 1062: 1060: 1049: 1043: 1040: 1034: 1033: 1015: 933:Conceptual space 903:BRAIN Initiative 888:Autonomous agent 878:Artificial brain 838:was proposed by 780:developed under 736:developed under 720:Michael Georgeff 565:with multilayer 472:Melanie Mitchell 454:machine learning 385:developed under 333:John R. Anderson 271: 262:Notable examples 203:at its core, or 185:computationalism 167:, as, e.g., the 104:John R. Anderson 82:Herbert A. Simon 21: 1530: 1529: 1525: 1524: 1523: 1521: 1520: 1519: 1505: 1504: 1477: 1472: 1471: 1463: 1459: 1413: 1412: 1408: 1363:Neural Networks 1360: 1359: 1355: 1346: 1345: 1341: 1294: 1293: 1289: 1273: 1272: 1268: 1252: 1251: 1247: 1225: 1224: 1220: 1212: 1205: 1204: 1200: 1191: 1189: 1185: 1178: 1177: 1173: 1164: 1160: 1130: 1129: 1125: 1110: 1106: 1097: 1093: 1083: 1081: 1073: 1072: 1068: 1058: 1056: 1051: 1050: 1046: 1041: 1037: 1030: 1017: 1016: 1012: 1007: 1002: 953:Knowledge level 873: 803:Society of Mind 768:spiking neurons 738:Dietrich Dörner 655:On Intelligence 601:Karl H. Pribram 541:Google DeepMind 264: 234:In traditional 179:, or similarly 149: 108:Gordon H. Bower 79: 28: 23: 22: 15: 12: 11: 5: 1528: 1526: 1518: 1517: 1507: 1506: 1503: 1502: 1490: 1476: 1475:External links 1473: 1470: 1469: 1457: 1406: 1353: 1339: 1287: 1266: 1245: 1218: 1198: 1171: 1158: 1139:(2): 151–180. 1123: 1104: 1091: 1066: 1044: 1035: 1028: 1009: 1008: 1006: 1003: 1001: 1000: 995: 993:Bayesian Brain 990: 985: 980: 975: 970: 965: 960: 955: 950: 945: 940: 935: 930: 925: 920: 915: 910: 905: 900: 895: 890: 885: 880: 874: 872: 869: 866: 865: 854: 848: 847: 840:Pentti Kanerva 836: 830: 829: 822: 814: 813: 806: 798: 797: 778: 772: 771: 760: 754: 753: 734: 728: 727: 716: 710: 709: 706: 700: 699: 684: 678: 677: 666: 660: 659: 618: 612: 611: 585: 579: 578: 555:Turing machine 547:neural network 543: 537: 536: 532: 526: 525: 518: 512: 511: 508:Boicho Kokinov 500: 494: 493: 486: 480: 479: 464: 458: 457: 450:classification 423: 417: 416: 405: 399: 398: 383: 377: 376: 361: 355: 354: 343: 337: 336: 325: 319: 318: 303: 297: 296: 293:Marcel A. Just 285: 279: 278: 275: 263: 260: 217:neural network 148: 145: 78: 75: 72:environments." 26: 24: 14: 13: 10: 9: 6: 4: 3: 2: 1527: 1516: 1513: 1512: 1510: 1500: 1495: 1491: 1488: 1483: 1479: 1478: 1474: 1467: 1461: 1458: 1453: 1449: 1445: 1441: 1437: 1433: 1429: 1425: 1421: 1417: 1410: 1407: 1402: 1398: 1394: 1390: 1386: 1382: 1377: 1372: 1368: 1364: 1357: 1354: 1349: 1343: 1340: 1335: 1331: 1327: 1323: 1319: 1315: 1311: 1307: 1303: 1299: 1291: 1288: 1282: 1277: 1270: 1267: 1261: 1256: 1249: 1246: 1241: 1237: 1233: 1229: 1222: 1219: 1211: 1210: 1202: 1199: 1184: 1183: 1175: 1172: 1168: 1162: 1159: 1154: 1150: 1146: 1142: 1138: 1134: 1127: 1124: 1120: 1118: 1113: 1108: 1105: 1101: 1095: 1092: 1080: 1076: 1070: 1067: 1054: 1048: 1045: 1039: 1036: 1031: 1029:9781138207929 1025: 1021: 1014: 1011: 1004: 999: 996: 994: 991: 989: 986: 984: 981: 979: 976: 974: 971: 969: 966: 964: 961: 959: 956: 954: 951: 949: 946: 944: 941: 939: 938:Deep learning 936: 934: 931: 929: 926: 924: 921: 919: 916: 914: 911: 909: 906: 904: 901: 899: 896: 894: 891: 889: 886: 884: 881: 879: 876: 875: 870: 863: 859: 858:Rodney Brooks 855: 853: 850: 849: 845: 841: 837: 835: 832: 831: 827: 826:Marvin Minsky 823: 821: 820: 816: 815: 811: 810:Marvin Minsky 807: 805: 804: 800: 799: 795: 791: 787: 783: 779: 777: 774: 773: 769: 765: 761: 759: 756: 755: 751: 747: 743: 739: 735: 733: 730: 729: 725: 721: 717: 715: 712: 711: 707: 705: 702: 701: 697: 693: 692:Stan Franklin 689: 686:implementing 685: 683: 680: 679: 675: 671: 667: 665: 662: 661: 657: 656: 651: 647: 643: 639: 635: 631: 630:Dileep George 627: 623: 619: 617: 614: 613: 609: 606: 602: 598: 594: 593:Riemann plane 590: 586: 584: 581: 580: 576: 575:deep learning 572: 568: 564: 560: 556: 552: 548: 544: 542: 539: 538: 533: 531: 528: 527: 523: 519: 517: 514: 513: 509: 505: 501: 499: 496: 495: 491: 487: 485: 482: 481: 477: 473: 469: 465: 463: 460: 459: 455: 451: 447: 443: 439: 435: 432: 428: 424: 422: 419: 418: 414: 410: 406: 404: 401: 400: 396: 392: 388: 387:Fernand Gobet 384: 382: 379: 378: 374: 370: 366: 365:Rony Novianto 363:developed by 362: 360: 357: 356: 352: 348: 345:developed at 344: 342: 339: 338: 334: 330: 327:developed at 326: 324: 321: 320: 316: 312: 308: 305:developed by 304: 302: 299: 298: 294: 290: 287:developed at 286: 284: 281: 280: 276: 273: 272: 267: 261: 259: 257: 253: 249: 245: 241: 237: 232: 230: 226: 222: 218: 214: 213:connectionism 210: 206: 205:decentralized 202: 198: 194: 190: 186: 182: 178: 175:based on the 174: 170: 166: 165:generic rules 162: 158: 157:connectionist 154: 146: 144: 142: 138: 134: 133:computational 130: 125: 120: 118: 114: 109: 105: 101: 99: 95: 91: 87: 86:Ed Feigenbaum 83: 76: 74: 73: 68: 63: 61: 57: 53: 49: 45: 41: 37: 33: 19: 1501:at Wikiquote 1460: 1419: 1415: 1409: 1366: 1362: 1356: 1342: 1301: 1297: 1290: 1269: 1248: 1231: 1227: 1221: 1208: 1201: 1190:. Retrieved 1181: 1174: 1166: 1161: 1136: 1132: 1126: 1115: 1107: 1094: 1082:. Retrieved 1069: 1057:. Retrieved 1047: 1038: 1019: 1013: 958:Neocognitron 948:Image schema 943:Google Brain 861: 824:proposed by 817: 808:proposed by 801: 782:Allen Newell 682:IDA and LIDA 653: 652:in his book 650:Jeff Hawkins 626:Jeff Hawkins 277:Description 265: 240:intelligence 233: 188: 150: 147:Distinctions 123: 121: 117:Allen Newell 102: 94:human memory 80: 70: 64: 60:Allen Newell 31: 29: 1084:11 February 1059:11 February 640:. HTM is a 634:algorithmic 605:associative 551:video games 456:community. 442:James Albus 431:associative 351:Lars Ludwig 307:James Albus 231:structure. 197:centralized 137:intelligent 1369:: 85–117. 1192:2017-02-07 1121:1983/2013. 1005:References 786:John Laird 732:Psi-Theory 642:biomimetic 563:Q-learning 530:Framsticks 484:DAYDREAMER 427:cerebellum 96:and human 62:in 1990. 36:human mind 1376:1404.7828 1334:205242740 1281:1410.5401 1260:1312.5602 1215:(Thesis). 862:cognitive 638:neocortex 252:bottom-up 225:atomistic 201:processor 48:cognition 1509:Category 1444:23197532 1401:11715509 1393:25462637 1326:25719670 871:See also 792:and the 256:top-down 221:holistic 189:a priori 153:symbolic 98:learning 1452:1673514 1424:Bibcode 1416:Science 1306:Bibcode 1153:9709702 750:Germany 746:Bamberg 740:at the 694:at the 474:at the 462:Copycat 452:in the 409:Ron Sun 403:CLARION 229:modular 193:CLARION 171:(e.g., 77:History 1450:  1442:  1399:  1391:  1332:  1324:  1298:Nature 1151:  1026:  664:CoJACK 608:memory 506:under 434:memory 381:CHREST 349:under 331:under 161:hybrid 44:models 1448:S2CID 1397:S2CID 1371:arXiv 1330:S2CID 1276:arXiv 1255:arXiv 1213:(PDF) 1186:(pdf) 1149:S2CID 670:ACT-R 323:ACT-R 283:4CAPS 244:learn 181:ACT-R 159:, or 52:ACT-R 1440:PMID 1389:PMID 1322:PMID 1086:2024 1061:2024 1024:ISBN 784:and 776:Soar 674:JACK 628:and 516:FORR 498:DUAL 470:and 421:CMAC 359:ASMO 311:NIST 274:Name 223:and 173:Soar 90:EPAM 65:The 56:SOAR 1432:doi 1420:338 1381:doi 1314:doi 1302:518 1236:doi 1141:doi 864:). 842:at 788:at 744:in 714:PRS 668:An 599:by 577:.) 466:by 440:by 411:at 389:at 309:at 291:by 113:ACT 100:). 1511:: 1446:. 1438:. 1430:. 1418:. 1395:. 1387:. 1379:. 1367:61 1365:. 1328:. 1320:. 1312:. 1300:. 1232:45 1230:. 1147:. 1137:11 1135:. 1114:. 1077:. 828:. 812:. 796:. 752:. 748:, 726:. 698:. 524:. 510:. 478:. 397:. 367:, 353:. 335:. 317:. 238:, 236:AI 155:, 88:, 30:A 1454:. 1434:: 1426:: 1403:. 1383:: 1373:: 1350:. 1336:. 1316:: 1308:: 1284:. 1278:: 1263:. 1257:: 1242:. 1238:: 1195:. 1155:. 1143:: 1119:, 1098:" 1088:. 1063:. 1032:. 20:)

Index

Cognitive architectures
human mind
computational cognitive science
models
cognition
ACT-R
SOAR
Allen Newell
Institute for Creative Technologies
Herbert A. Simon
Ed Feigenbaum
EPAM
human memory
learning
John R. Anderson
Gordon H. Bower
ACT
Allen Newell
intelligent agents
computational
intelligent
agent architectures
symbolic
connectionist
hybrid
generic rules
Information Processing Language
Soar
unified theory of cognition
ACT-R

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