Commonsense Bibliography

 

Collected by Push Singh and Erik T. Mueller

Contributions from: Barbara Barry, Leiguang Gong, Hugo Liu, and Stefan Marti

 

Last updated 2002-02-11

 

Table of contents

 

1      Recent overviews of the problem of common sense

2      Classics

3      Critiques and essays

4      Cyc

4.1        Cyc overviews

4.2        Cyc criticisms and evaluations

5      Architectures for common sense

5.1        The society of mind

5.2        The cognition and affect project

5.3        Blackboard systems

5.4        Other heterogeneous architectures

5.5        Soar

5.6        Other unified architectures

6      Logical formalisms for commonsense reasoning

6.1        Overviews

6.2        Situation calculus

6.3        Event calculus

6.4        Language of the causal calculator

6.5        Features and fluents

6.6        Default reasoning

6.7        Circumscription

7      Other mechanisms for common sense

7.1        Analogy and metaphor

7.2        Case-based reasoning

7.3        Marker passing

7.4        Reformulation

7.5        Lexical semantics

7.6        Connectionism

7.7        Situated action

8      Realms of common sense

8.1        Time

8.2        Space

8.3        Physics

8.4        Egg cracking

8.5        Frames and scripts

8.6        Plans and Goals

8.7        Beliefs, desires, and intentions

8.8        Interpersonal relations

8.9        Emotions

8.10      Personality

8.11      Plot structures

8.12      Economics

8.13      Vision

8.14      Gesture

8.15      Metaplanning and reflection

8.16      Context

8.17      Causality

8.18      Creativity and invention

9      Acquisition of common sense

9.1        Distributed human projects

9.2        Sketching

9.3        Learning structural representations

9.4        Sensory grounded learning

10     Applications of common sense

10.1      Context-aware agents

10.2      The Semantic Web

10.3      Story understanding

10.4      Robots

11     Results from psychology and neuroscience

12     Popular books

13     Web resources

 

1           Recent overviews of the problem of common sense

 

Minsky, Marvin (2000). Commonsense-based interfaces. Communications of the ACM, 43(8), 67-73.

http://www.acm.org/pubs/citations/journals/cacm/2000-43-8/p66-minsky/

http://commonsense.media.mit.edu/minsky.pdf

 

Minsky, Marvin (forthcoming). The Emotion Machine (Part 5).

http://web.media.mit.edu/~minsky/E5/eb5.html

 

Singh, Push (2002). The Open Mind Common Sense project.

http://openmind.media.mit.edu/Kurzweil.htm

http://www.kurzweilai.net/meme/frame.html?main=/articles/art0371.html

 

Davis, Ernest (1998). The naive physics perplex. AI Magazine, 19(4), 51-79.

http://csdocs.cs.nyu.edu/Dienst/UI/2.0/Describe/ncstrl.nyu_cs%2FTR1997-738

2           Classics

 

McCarthy, John (1959). Programs with common sense.

http://www-formal.stanford.edu/jmc/mcc59.html

 

McCarthy, John (1990). Formalizing common sense. Norwood, NJ: Ablex.

http://www-formal.stanford.edu/jmc/

 

Minsky, Marvin (1968). Introduction. In Marvin L. Minsky (Ed.), Semantic information processing (pp. 1-32). Cambridge, MA: MIT Press.

 

Minsky, Marvin (1974). A framework for representing knowledge (AI Laboratory Memo 306). Artificial Intelligence Laboratory, Massachusetts Institute of Technology.

ftp://publications.ai.mit.edu/ai-publications/0-499/AIM-306.ps

http://www.media.mit.edu/~minsky/papers/Frames/frames.html

 

Minsky, Marvin (1986). The society of mind. New York: Simon and Schuster.

3           Critiques and essays

 

Birnbaum, Lawrence (1991). Rigor mortis: a response to Nilsson's "Logic and artificial intelligence." Artificial Intelligence, 47, 57-77.

 

Clancey, W. J., Smoliar, S. W., and Stefik, M. J. (Eds.) (1994). Contemplating minds: A forum for artificial intelligence. Cambridge, MA: MIT Press.

 

Davis, R., Shrobe, H., & and Szolovits, P. (1993). What is a Knowledge Representation? AI Magazine, 17-33.

http://medg.lcs.mit.edu/ftp/psz/k-rep.html

 

Giunchiglia, Fausto (1995). An epistemological science of common sense. Book review of John McCarthy's Formalizing Common Sense. Artificial Intelligence, 77, 371-392.

http://citeseer.nj.nec.com/giunchiglia96epistemological.html

 

Hayes, P. J. (1977). In defence of logic. Proceedings of the Fifth International Joint Conference on Artificial Intelligence.

 

McCarthy, John. The well-designed child.

http://www-formal.stanford.edu/jmc/child1.html

 

McCarthy, John (1996). From here to human-level AI.

http://www-formal.stanford.edu/jmc/human.html

 

McDermott, D. (1987). A critique of pure reason. Computational Intelligence, 3, 151-160.

Mueller, Erik T. (1999). Prospects for in-depth story understanding by computer. CogPrints cog00000554.

http://www.media.mit.edu/~mueller/papers/storyund.html


Nilsson, Nils. J. (1991). Logic and artificial intelligence. Artificial Intelligence, 47, 31-56.

4           Cyc

 

4.1         Cyc overviews

 

Guha, Ramanathan, & Lenat, Douglas (1990). Cyc: A midterm report. AI Magazine, 11(3), 32-59.

 

Guha, Ramanathan, & Lenat, Douglas (1994). Enabling agents to work together. Communications of the ACM, 37(7),127-142.

http://www.acm.org/pubs/citations/journals/cacm/1994-37-7/p126-guha/

 

Lenat, Douglas (1995). CYC: A large-scale investment in knowledge infrastructure. Communications of the ACM, 38(11).

 

Lenat, Douglas (1997). Cyc Upper Ontology.

http://www.cyc.com/cyc-2-1/index.html

 

Lenat, Douglas, & Guha, Ramanathan (1990). Building large knowledge-based systems. Reading, MA: Addison-Wesley.

 

Lenat, Douglas, & Guha, Ramanathan (1991). The evolution of CycL, the Cyc representation language. SIGART Bulletin, 2(3), 84-87.

 

4.2         Cyc criticisms and evaluations

 

Guha, Ramanathan, & Lenat, Douglas (1993). Re: CycLing paper reviews, Artificial Intelligence, 61(1), 149-174.

 

Locke, Christopher (1990). Common knowledge or superior Ignorance?

http://www.panix.com/~clocke/ieee.html

 

Mahesh, Kavi, Nirenburg, Sergei, Cowie, Jim, & Farwell, David (1996). An assessment of Cyc for natural language processing (Technical Report MCCS 96-302). Computing Research Laboratory, New Mexico State University, Las Cruces, New Mexico.

http://crl.nmsu.edu/Research/Pubs/MCCS/Postscript/mccs-96-302.ps

 

Pratt, Vaughan (1994). Cyc report.

http://boole.stanford.edu/cyc.html

http://www.cs.umbc.edu/~narayan/proj/cyc-critic.html

 

Stefik, Mark J., & Smoliar, Stephen W. (1993). The commonsense reviews. Artificial Intelligence, 61, 37-179.

http://www1.elsevier.nl/inca/publications/store/5/0/5/6/0/1/

http://www.cs.brandeis.edu/~brendy/CYC_report.txt

5           Architectures for common sense

 

5.1         The society of mind

 

Minsky, Marvin (1986). The society of mind. New York: Simon and Schuster.

 

Minsky, Marvin (forthcoming). The Emotion Machine.

http://web.media.mit.edu/~minsky/E1/eb1.html

http://web.media.mit.edu/~minsky/E2/eb2.html

http://web.media.mit.edu/~minsky/E3/eb3.html

http://web.media.mit.edu/~minsky/E4/eb4.html

http://web.media.mit.edu/~minsky/E5/eb5.html

 

Minsky, Marvin (1981). Jokes and their relation to the cognitive unconscious. In Vaina and Hintikka (Eds.), Cognitive Constraints on Communication. Reidel.

http://web.media.mit.edu/~minsky/papers/jokes.cognitive.txt

 

Minsky, Marvin (1991). Logical vs. analogical or symbolic vs. connectionist or neat vs. scruffy. AI Magazine, Summer 1991.

http://web.media.mit.edu/~minsky/papers/SymbolicVs.Connectionist.html

 

Minsky, Marvin (1994). Negative expertise. International Journal of Expert Systems, 7(1), 13-19.

http://web.media.mit.edu/~minsky/papers/NegExp.mss.txt

 

5.2         The cognition and affect project

 

Beaudoin, Luc P. (1994). Goal processing in autonomous agents.

http://www.cs.bham.ac.uk/research/cogaff/0-INDEX81-95.html#38

 

Sloman, Aaron (1981). Why robots will have emotions. Proceedings of the Seventh International Joint Conference on Artificial Intelligence.

http://www.cs.bham.ac.uk/research/cogaff/0-INDEX81-95.html#36

 

Sloman, Aaron (1998). Damasio, Descartes, alarms and meta-management.

http://www.cs.bham.ac.uk/research/cogaff/0-INDEX96-99.html#36

 

Sloman, Aaron (1998). What’s an AI toolkit for?

http://www.cs.bham.ac.uk/research/cogaff/0-INDEX96-99.html#34

 

5.3         Blackboard systems

 

Carver, N., & Lesser, V. (1994). Evolution of blackboard control architectures. Expert Systems with Applications 7, 1-30.

http://citeseer.nj.nec.com/carver92evolution.html

 

Engelmore, R. and Morgan, T. (1988). Blackboard systems. Reading, MA: Addison-Wesley.

 

Hayes-Roth, B. (1985). A blackboard architecture for control. Artificial Intelligence, 26, 251-321.

 

Nii, H. P. (1986). Blackboard Systems: The blackboard model of problem solving and the evolution of blackboard architectures. AI Magazine, 7(2), 38-53.

 

5.4         Other heterogeneous architectures

 

Mueller, Erik T. (1990). Daydreaming in humans and machines: A computer model of the stream of thought. Norwood, NJ: Ablex/Intellect.
ftp://ftp.cs.ucla.edu/tech-report/198_-reports/870017.pdf

 

Mueller, Erik T. (1998). Natural language processing with ThoughtTreasure. New York: Signiform.

http://www.signiform.com/tt/book/

 

Riecken, Doug (1994). M: An architecture of integrated agents. Communications of the ACM, 37(7), 107-116.

 

Singh, Push (1999). Big list of mental agents for common sense thinking.

http://www.media.mit.edu/people/push/agencies.html

 

5.5         Soar

 

Laird, J.E., & Rosenbloom, P.S. (1996). The evolution of the Soar cognitive architecture. In T. Mitchell (Ed.) Mind Matters.

http://citeseer.nj.nec.com/laird94evolution.html

 

Lehman, J.F., Laird, J.E., & Rosenbloom, P.S. (1996). A gentle introduction to Soar, an architecture for human cognition. In S. Sternberg & D. Scarborough (Eds.) Invitation to Cognitive Science (Volume 4).

http://www.cse.msu.edu/~cse841/papers/Soar.pdf

 

Newell A., & Simon, H. A. (1963). GPS, a program that simulates human thought. In E. A. Feigenbaum and J. Feldman, editors, Computers and Thought, pages 279-293. New York: McGraw-Hill.

 

Newell, A. (1990). Unified Theories of Cognition. Cambridge, MA: Harvard University Press.

 

Rosenbloom, P.S., Laird, J.E. & Newell, A. (1993). The Soar Papers: Readings on Integrated Intelligence. Cambridge, MA: MIT Press.

 

5.6         Other unified architectures

 

Anderson, John R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.

6           Logical formalisms for commonsense reasoning

 

6.1         Overviews

 

Davis, Ernest (1990). Representations of Commonsense Knowledge. San Mateo, CA: Morgan Kaufmann.

http://www.mkp.com/books_catalog/catalog.asp?ISBN=1-55860-033-7

 

Hobbs, Jerry R., & Moore, Robert C. (Eds.). (1985). Formal theories of the commonsense world. Norwood, NJ: Ablex.

 

McCarthy, John (1990). Formalizing common sense. Norwood, NJ: Ablex.

http://www-formal.stanford.edu/jmc/

 

6.2         Situation calculus

 

McCarthy, John, & Hayes, Patrick J. (1969). Some philosophical problems from the standpoint of artificial intelligence. In D. Michie & B. Meltzer (Eds.), Machine intelligence 4. Edinburgh, Scotland: Edinburgh University Press.

http://www-formal.stanford.edu/jmc/mcchay69/mcchay69.html

 

Reiter, Raymond (2001). Knowledge in action: Logical foundations for specifying and implementing dynamical systems. Cambridge, MA: MIT Press.

 

6.3         Event calculus

 

Kowalski, R. & Sergot, M. J. (1986). A logic-based calculus of events. New Generation Computing, 4, 67-95.

 

Shanahan, Murray (1997). Solving the frame problem. Cambridge, MA: MIT Press.

 

Shanahan, Murray (1999). The Event Calculus explained. In M. J. Wooldridge & M. Veloso (Eds.), Artificial intelligence today (pp. 409-430). Heidelberg: Springer-Verlag.

http://www-ics.ee.ic.ac.uk/~mpsha/ECExplained.ps.Z

 

6.4         Language of the causal calculator

 

Akman, Varol, Erdogan, Selim, & Lee, Joohyung, & Lifschitz, Vladimir (2001). A representation of the traffic world in the language of the causal Calculator. Fifth Symposium on Logical Formalizations of Commonsense Reasoning.

http://www.cs.nyu.edu/faculty/davise/commonsense01/final/akman.ps

 

Lee, Joohyung, Lifschitz, Vladimir, & Turner, Hudson (2001). A representation of the zoo world in the language of the causal calculator. Fifth Symposium on Logical Formalizations of Commonsense Reasoning.

http://www.cs.nyu.edu/faculty/davise/commonsense01/final/lee.ps

 

McCain, N., & Turner, H. (1997). Causal theories of action and change. Proceedings of the Fourteenth National Conference on Artificial Intelligence.

http://citeseer.nj.nec.com/mccain97causal.html

 

McCain, N., & Turner, H. (1995). A causal theory of ramifications and qualifications. Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence.

http://citeseer.nj.nec.com/mccain95causal.html

 

6.5         Features and fluents

 

Sandewall, Erik (1994). Features and fluents: The representation of knowledge about dynamical systems (Volume I). Oxford University Press.

 

Doherty, Patrick, Gustafsson, Joakim, Karlsson, Lars, & Kvarnstrom, Jonas (1998). TAL: Temporal Action Logics language specification and tutorial.

http://www.ep.liu.se/ea/cis/1998/015/

 

6.6         Default reasoning

 

de Kleer, J. (1986). An assumption based truth maintenance system. Artificial Intelligence, 28, 127-162.

 

Doyle, J. (1979). A truth maintenance system. Artificial Intelligence, 12, 231-272.

 

McDermott, D., & Doyle. J. (1980). Non-monotonic logic I. Artificial Intelligence 13, 41-72.

 

Reiter, R. (1980). A logic for default reasoning. Artificial Intelligence 13, 81-132.

 

6.7         Circumscription

 

Lifschitz, Vladimir (1994). Circumscription. In Handbook of logic in AI and logic programming (Volume 3). Oxford University Press.

http://www.cs.utexas.edu/users/vl/mypapers/circumscription.ps

 

McCarthy, John (1980). Circumscription—A form of non-monotonic reasoning. Journal of Artificial Intelligence, 13, 27-39.

http://www-formal.stanford.edu/jmc/circumscription.html

 

7           Other mechanisms for common sense

 

7.1         Analogy and metaphor

 

Falkenhainer, B., Forbus, K.D., & Gentner, D. (1990). The structure-mapping engine: Algorithm and examples. Artificial Intelligence, 41, 1-63.

http://citeseer.nj.nec.com/falkenhainer89structuremapping.html

 

Forbus, K. D., Gentner, D., Markman, A. B., & Ferguson, R. W. (1998). Analogy just looks like high-level perception: Why a domain-general approach to analogical mapping is right. Journal of Experimental and Theoretical Artificial Intelligence, 10(2), 231-257.

http://www.psych.nwu.edu/psych/people/faculty/gentner/pdfs%20papers/forbus-gentner-98.pdf

 

Gentner, D. (2001). Spatial metaphors in temporal reasoning. In M. Gattis (Ed.), Spatial schemas in abstract thought (pp. 203-222). Cambridge, MA: MIT Press.

http://www.psych.nwu.edu/psych/people/faculty/gentner/pdfs%20papers/spatial%20schemas.2001.pdf

 

Gentner, D., Bowdle, B., Wolff, P., & Boronat, C. (2001). Metaphor is like analogy. In D. Gentner, K. J. Holyoak, & B. N. Kokinov (Eds.), The analogical mind: Perspectives from cognitive science (pp. 199-253). Cambridge, MA: MIT Press.

http://www.psych.nwu.edu/psych/people/faculty/gentner/pdfs%20papers/gentner-a2k-01.pdf

 

Lakoff G. & Johnson M. (1990) Metaphors we live by. University of Chicago Press.

 

7.2         Case-based reasoning

 

Carbonell, J. (1986). Derivational analogy: A theory of reconstructive problem solving and expertise acquisition. In R.S. Michalski et al. (Eds.), Machine intelligence: An AI approach.

 

Hammond, C. (1989). Case-based planning: Viewing planning as a memory task. San Diego: Academic Press.

 

Hammond, K. J. (1990). Explaining and repairing plans that fail. Artificial Intelligence, 45(3), 173-228.

 

Kolodner, J. (1992). An introduction to case-based reasoning. Artificial Intelligence Review, 6, 3-34.

 

Kolodner, J. (1993). Case-Based Reasoning. San Mateo, CA: Morgan Kaufman.

 

Veloso, M. M., & Carbonell, J. G. (1993). Derivational analogy in Prodigy: Automating case acquisition, storage, and utilization. Machine Learning, 10 , 249-278.

 

7.3         Marker passing

 

Norvig, Peter (1987). Unified theory of inference for text understanding (Report No. UCB/CSD 87/339). Berkeley, CA: University of California, Computer Science Division.
http://sunsite.berkeley.edu/Dienst/UI/2.0/Describe/ncstrl.ucb/CSD-87-339


Norvig, Peter (1989). Marker passing as a weak method for text inferencing. Cognitive Science, 13, 569-620.

 

Hendler, J. (1988). Integrating marker-passing and problem-solving. Hillsdale, NJ: Erlbaum.

 

7.4         Reformulation

 

Amarel, Saul (1968). On representations of problems of reasoning about actions. In Michie (Ed.), Machine Intelligence 3. Edinburgh University Press.

 

Singh, Push (1998). Failure-directed reformulation (M.Eng. thesis).

http://web.media.mit.edu/~push/reformulation.ps

 

7.5         Lexical semantics

 

Fellbaum, Christiane (Ed.). (1998). WordNet: An electronic lexical database. Cambridge, MA: MIT Press.

http://www.cogsci.princeton.edu/~wn/papers/

 

Jackendoff, R. (1983). Semantics and cognition. Cambridge, MA, MIT Press.

 

Lyons, J. (1977). Semantics (Volumes I and II). Cambridge: Cambridge University Press.

 

Mel'cuk, Igor & Polguere, Alain (1987). A formal lexicon in the meaning-text theory (or How to do lexica with words). Computational Linguistics, 13(3-4), 261-275.

 

Pustejovsky, J. (1995). The generative lexicon. Cambridge, MA: MIT Press.

 

7.6         Connectionism

 

Minsky, Marvin, & Papert, Seymour (1988). Perceptrons (Expanded edition). Cambridge, MA: MIT Press.

Miikkulainen, R. (1993). Subsymbolic natural language processing: An integrated model of scripts, lexicon, and memory. Cambridge, MA: MIT Press.

Sun, Ron (1994). Integrating rules and connectionism for robust commonsense reasoning. New York: Wiley.

 

7.7         Situated action

 

Agre, Philip E. (1997). Computation and human experience. Cambridge University Press.

 

Suchman, Lucy A. (1987). Plans and situated action. Cambridge University Press.

8           Realms of common sense

 

8.1         Time

 

Allen, J. F. (1983). Maintaining knowledge about temporal intervals. Communications of the ACM, 26(11), 832-843.

 

Allen, J. F. (1984). Towards a general theory of action and time, Artificial Intelligence 23, 123-154.

 

Allen, J. F., & Hayes, P. J. (1985). A common-sense theory of time. Proceedings of the Ninth International Joint Conference on Artificial Intelligence, 528-531.

 

Allen, J. F. (1991). Time and time again: The many ways to represent time. International Journal of Intelligent Systems 6(4), 341-356.

http://www.cs.rochester.edu/u/james/

(download ps)

 

Allen, J. F. (1991). Planning as temporal reasoning. Proceedings of 2nd Principles of Knowledge Representation and Reasoning, San Mateo, CA: Morgan Kaufmann.

http://www.cs.rochester.edu/u/james/kr91.pdf

 

ter Meulen, A. G. B. (1995). Representing time in natural language. Cambridge, MA: MIT Press.

 

8.2         Space

 

Davis, Ernest (1986). Representing and acquiring geographic knowledge. San Mateo, CA: Morgan Kaufman.

 

Davis, Ernest (1991). Lucid representations (Technical Report 565). Computer Science Department, New York University.

http://citeseer.nj.nec.com/davis94lucid.html

 

Davis, Ernest (1995). A highly expressive language of spatial constraints (Technical Report 714). Computer Science Department, New York University.

ftp://cs.nyu.edu/pub/tech-reports/tr714.ps.gz

 

Kuipers, B. J. (1978). Modeling spatial knowledge. Cognitive Science, 2, 129-153.

http://citeseer.nj.nec.com/kuipers78modeling.html

 

Kuipers, B. J. (2000). The spatial semantic hierarchy. Artificial Intelligence, 119, 191-233.

http://citeseer.nj.nec.com/kuipers00spatial.html

 

Mukerjee, Amitabha (1998). Neat vs. scruffy: A survey of computational models for spatial expressions. In Representation and processing of spatial expressions.
http://citeseer.nj.nec.com/250615.html

 

8.3         Physics

 

Hayes, P. J. (1979). Naive physics manifesto. Expert Systems in the Microelectronic Age. Edinburgh: Edinburgh University Press.

 

Hayes, P. J. (1985). The second naive physics manifesto. In J. R. Hobbs & R. C. Moore (Eds.), Formal theories of the commonsense world. Norwood, NJ: Ablex.

 

Hayes, P. J. (1985). Naive physics I: Ontology for liquids. In J. R. Hobbs & R. C. Moore (Eds.), Formal theories of the commonsense world. Norwood, NJ: Ablex.

 

Rieger, C., & Grinberg, M. (1977). The causal representation and simulation of physical mechanisms. Technical Report TR-495, Dept. of Computer Science, University of Maryland.

 

8.4         Egg cracking

 

Lifschitz, Vladimir (1998). Cracking an egg: An exercise in formalizing commonsense reasoning.

http://www.cs.utexas.edu/users/vl/mypapers/egg.ps

 

Morgenstern, Leora (2001). Mid-sized axiomatizations of commonsense problems: A case study in egg cracking. Studia Logica, 67, 333-384.

http://www.kluweronline.com/issn/0039-3215

 

Shanahan, Murray (1998). A logical formalisation of Ernie Davis's egg cracking problem.

http://www.dcs.qmw.ac.uk/~mps/egg_murray.ps.Z

 

8.5         Frames and scripts

 

Fillmore, C. (1968). The case for case. In E. Bach and R. Harms (Eds.), Universals in linguistic theory. New York: Holt, Reinhart and Winston.

 

Minsky, Marvin (1974). A framework for representing knowledge (AI Laboratory Memo 306). Artificial Intelligence Laboratory, Massachusetts Institute of Technology.

ftp://publications.ai.mit.edu/ai-publications/0-499/AIM-306.ps

http://www.media.mit.edu/~minsky/papers/Frames/frames.html

 

Mueller, Erik T. (1999). A database and lexicon of scripts for ThoughtTreasure.CogPrints cog00000555.

http://www.signiform.com/tt/htm/script.htm

 

Schank, R. C., and Abelson, R. P. (1977). Scripts, plans, goals, and understanding. Hillsdale, NJ: Erlbaum.

 

Wilks, Yorick (1975). A preferential, pattern-seeking, semantics for natural language inference. Artificial Intelligence. 6(1), 53-74.

 

8.6         Plans and Goals

 

Allen, James F., Kautz, Henry A., Pelavin, Richard N., & Tenenberg, Josh D. (1991). Reasoning about plans. San Mateo, CA: Morgan Kaufmann.

 

Schank, R. C., and Abelson, R. P. (1977). Scripts, plans, goals, and understanding. Hillsdale, NJ: Erlbaum.

 

Schank, Roger C., & Riesbeck, Christopher K. (1981). Inside computer understanding. Hillsdale, NJ: Erlbaum.

 

8.7         Beliefs, desires, and intentions

 

Bratman, M. E., Israel, D. J., and Pollack, M. E. (1988). Plans and resource-bounded practical reasoning. Computational Intelligence, 4(4).

http://citeseer.nj.nec.com/bratman88plans.html

 

Cohen, Philip R., and Levesque, Hector J. (1990). Intention is choice with commitment. Artificial Intelligence, 42, 213-261.

 

Fagin, Ronald, Halpern, Joseph Y., Moses, Yoram, & Vardi, Moshe Y. (1995). Reasoning About Knowledge. Cambridge, MA: MIT Press.

 

Halpern, J. and Moses, Y. (1984). Knowledge and common knowledge in a distributed environment, Proceedings of the Third ACM Symposium on Principles of Distributed Computing, 50-61. New York: ACM.

http://citeseer.nj.nec.com/halpern84knowledge.html

 

Lakemeyer, G. and Levesque, H. J. (1998). AOL: a logic of acting, sensing, knowing, and only knowing, Proceedings of the Sixth International Conference on Principles of Knowledge Representation and Reasoning. San Mateo, CA: Morgan Kaufmann.

 

Rao, A.S., & Georgeff, M. P. (1991). Modeling rational agents within a BDI-architecture. In J. Allen, R. Fikes, and E. Sandewall (Eds.), Proceedings of the Second International Conference on Principles of Knowledge Representation and Reasoning (pp. 473-484). San Mateo, CA: Morgan Kaufmann.

http://citeseer.nj.nec.com/rao91modeling.html

 

Smedslund, Jan (1997). The structure of psychological common sense. Mahwah, NJ: Erlbaum.

 

8.8         Interpersonal relations

 

Heider, Fritz (1958). The psychology of interpersonal relations. Hillsdale, NJ: Erlbaum.

 

Schank, R. C., and Abelson, R. P. (1977). Scripts, plans, goals, and understanding. Hillsdale, NJ: Erlbaum.

 

8.9         Emotions

 

Dyer, Michael G. (1987). Emotions and their computations: Three computer models. Cognition and Emotion, 1(3), 323-347.

 

Minsky, Marvin (forthcoming). The Emotion Machine.

http://web.media.mit.edu/~minsky/E1/eb1.html

http://web.media.mit.edu/~minsky/E2/eb2.html

http://web.media.mit.edu/~minsky/E3/eb3.html

http://web.media.mit.edu/~minsky/E4/eb4.html

http://web.media.mit.edu/~minsky/E5/eb5.html

 

O'Rorke, P., and Ortony, A. (1994). Explaining emotions. Cognitive science, 18(2), 283-323.

Ortony, A., Clore, G. L., and Collins, A. (1988). The cognitive structure of emotions. New York: Cambridge University Press.

 

Sloman, Aaron (2001). Beyond shallow models of emotion. Cognitive Processing, 1(1).