HOME   ::   Back to the Paper   ::   References

de Jong, E. D. (2000) Autonomous Formation of Concepts and Communication. PhD thesis, Vrije Universiteit Brussel.

References (may not be complete)  [Original format]  [Sort by year]  [Sort by author]  [Sort by citations]

Ackley, D. H., & Littman, M. L. (1994). Altruism in the evolution of communication. In R. A. Brooks & P. Maes (Eds.), Proceedings of the fourth international workshop on the synthesis and simulation of living systems. Cambridge, MA: The MIT Press (A Bradford Book).

Google UIUC

Agre, P., & Chapman, D. (1987). Pengi: An implementation of a theory of activity. In Proceedings aaai-87. San Mateo, CA: Morgan Kaufmann.

Google

Albus, J. (1981). Brains, behavior, and robotics. Peterborough, NH: Byte Books.

Google

Bala, J., De Jong, K., Huang, J., Vafaie, H., & Wechsler, H. (1996). Using learning to facilitate the evolution of features for recognizing visual concepts. Evolutionary Computation, 4 (3).

Google

Beer, R. D., Chiel, H. J., & Sterling, L. S. (1990). A biological perspective on autonomous agent design. In P. Maes (Ed.), Designing autonomous agents (pp. 169--185). The MIT Press: Cambridge, MA.

Google

Beer, R. D., & Gallagher, J. C. (1992). Evolving dynamical neural networks for adaptive behavior. Adaptive Behavior, 1 (1).

Google

Bellman, R. (1957). Dynamic programming. Princeton, N.J.: Princeton University Press.

Google

Belpaeme, T. (1999). Evolution of visual feature detectors. In Proceedings of the first european workshop on evolutionary computation in image analysis and signal processing (evoiasp99, g¨oteborg, sweden). UK.

Google

Bentley, J. L. (1975). Multidimensional binary search trees used for associative searching. Communications of the ACM, 18 (9), 509--517.

Google

Billard, A., & Hayes, G. (1997). Learning to communicate through imitation in autonomous robots. In Proceedings of the 7th international conference on artificial neural networks icann 97. Springer-Verlag.

Google

Billard, A., & Hayes, G. (1999). Drama, a connectionist architecture for control and learning in autonomous robots. Adaptive Behavior, 7 (1).

Google

Blair, A. D., & Pollack, J. B. (1997). Analysis of dynamical recognizers. Neural Computation, 9 (5), 1127--1142.

Google

Bonabeau, E., Theraulaz, G., Deneubourg, J.-L., Aron, S., & Camazine, S. (1997). Self-organization in social insects. Trends in Ecology and Evolution, 12 (5), 188-193.

Google

Cannon, W. B. (1932). The wisdom of the body. New York: Norton.

Google

Changeux, J.-P. (1985). Neuronal man. New York: Pantheon Books.

Google

Chapman, D., & Kaelbling, L. P. (1991). Input generalization in delayed reinforcement learning: An algorithm and performance comparisons. In J. Mylopoulos & R. Reiter. (Eds.), Proceedings of the twelfth international joint conference on artificial intelligence (ijcai-91) (pp. 726--731). San Mateo, Ca.: Morgan Kaufmann.

Google

Clancey, W. J. (1997). Situated cognition: on human knowledge and computer representations. Cambridge, UK: Cambridge University Press.

Google

Crites, R. H., & Barto, A. G. (1996). Improving elevator performance using reinforcement learning. In D. S. Touretzky, M. C. Mozer, & M. E. Hasselmo (Eds.), Advances in neural information processing systems (Vol. 8, pp. 1017--1023). The MIT Press.

Google

Davidoff, J., Davies, I., & Roberson, D. (1999). Colour categories in a stone-age tribe. Nature, 398, 203,204.

Google

De Boer, B. (1999). Self-organisation in vowel systems. Unpublished doctoral dissertation, Vrije Universiteit Brussel, Brussels, Belgium.

Google UIUC

De Jong, E. D. (1997a). An accumulative exploration method for reinforcement learning. In S. Sen (Ed.), Proceedings of the aaai'97 workshop on multiagent learning, available as aaai technical report ws-97-03 (p. 19-24). Menlo Park, California: AAAI Press.

Google

De Jong, E. D. (1997b). Multi-agent coordination by communication of evaluations. In M. Boman & W. V. de Velde (Eds.), Proceedings of the 8th european workshop on modelling autonomous agents in a multi-agent world maamaw'97. Berlin: Springer-Verlag.

Google UIUC

De Jong, E. D. (1999). Autonomous concept formation. In Proceedings of the sixteenth international joint conference on artificial intelligence ijcai'99 (p. 344-349). San Francisco, CA: Morgan Kaufmann.

Google UIUC

De Jong, E. D., & Steels, L. (1999). Generation and selection of sensory channels. In Evolutionary image analysis, signal processing and telecommunications first european workshops, evoiasp'99 and euroectel'99 joint proceedings (p. 90-100). Berlin: Springer-Verlag.

Google

De Jong, E. D., & Vogt, P. (1998). How Should a Robot Discriminate Between Objects? A comparison between two methods. In Proceedings of the fifth international conference of the society for adaptive behavior sab'98 (Vol. 5, p. 86-91). Cambridge, MA: The MIT Press.

Google

Di Paolo, E. A. (1997). Social coordination and spatial organization: Steps towards the evolution of communication. In P. Husbands & I. Harvey (Eds.), Proceedings of the 4th european conference on artificial life ecal'97. Cambridge, MA: The MIT Press (A Bradford Book).

Google UIUC

Drescher, G. L. (1991). Made-up minds. a constructivist approach to artificial intelligence. Cambridge, MA: The MIT Press.

Google

Duda, R., & Hart, P. (1973). Pattern recognition and scene analysis. John Wiley and Sons.

Google

Ebner, M., & Zell, A. (1999). Evolving a task specific image operator. In R. Poli, H.-M. Voigt, S. Cagnoni, D. Corne, G. D. Smith, & T. C. Fogarty (Eds.), Evolutionary image analysis, signal processing and telecommunications: First european workshop, evoiasp'99 and euroectel'99 (Vol. 1596, pp. 74--89). Goteborg, Sweden: SpringerVerlag.

Google

Eco, U. (1976). A theory of semiotics. Bloomington: Indiana University Press.

Google

Edelman, G. (1987). Neural darwinism. New York: Basic Books Inc.

Google

Elman, J. L. (1995). Language as a dynamical system. In R. F. Port & T. Van Gelder (Eds.), Mind as motion: Explorations in the dynamics of cognition (p. 195-225). MIT Press.

Google UIUC

Finin, T., Fritzson, R., McKay, D., & McEntire, R. (1994). Kqml a language and protocol for knowledge and information exchange (Tech. Rep. No. CS-94-02). Computer Science Department, University of Maryland, UMBC Baltimore MD 21228: Computer Science Department, University of Maryland and Valley Forge Engineering Center, Unisys Corporation.

Google

Finkel, R. A., & Bentley, J. L. (1974). Quad trees: A data structure for retrieval on composite keys. Acta Informatica, 4 (1), 1--9.

Google

Fipa content language library. (1999). Geneva, Switzerland. (URL: http://www.fipa.org)

Google

Fodor, J. A. (1998). Concepts: Where cognitive science went wrong. Oxford: Clarendon Press.

Google

Foley, W. A. (1997). Anthropological linguistics: An introduction. Blackwell publishers.

Google

Friedman, J. H., Bentley, J. L., & Finkel, R. A. (1977). An Algorithm for Finding Best Matches in Logarithmic Expected Time. ACM Transactions on Mathematical Software, 3 (3), 209--226.

Google

Fritzke, B. (1997, april). Some competitive learning methods. (Institute for Neural Computation,Ruhr-Universit¨at Bochum)

Google

Geman, S., Bienenstock, E., & Doursat, R. (1992). Neural networks and the bias/variance dilemma. Neural Computation, 4 (1), 1--58.

Google

Gennari, J., Langley, P., & Fisher, D. (1989). Models of incremental concept formation. In J. Carbonell (Ed.), Machine learning: Paradigms and methods. MIT / Elsevier.

Google UIUC

Gordon, D., & desJardins, M. (1995). Evaluations and selection of biases in machine learning. Machine Learning, 20 (1/2), 5-22.

Google

Harnad, S. (1990). The symbol grounding problem. Physica D, 42 (?), 335--346.

Google UIUC

Hauser, M. D. (1997). The evolution of communication. Cambridge, MA: The MIT Press.

Google UIUC

Holland, J. H. (1983). Escaping brittleness. In Proceedings Second International Workshop on Machine Learning (p. 92-95).

Google

Houk, J. C., Adams, J. L., & Barto, A. G. (1995). Models of information processing in the basal ganglia. In J. L. D. J. C. Houk & D. G. Beiser (Eds.), (p. 249-270). Cambridge, MA: MIT Press.

Google

Hurford, J. (1989). Biological evolution of the saussurean sign as a component of the language acquisition device. Lingua 77, 187-222.

Google UIUC

Huttenlocher, P. R. (1990). Morphometric study of human cerebral cortex development. Neuropsychologia, 28, 517-527.

Google

Jackins, C. L., & Tanimoto, S. L. (1980). Oct-trees and their use in representing three-dimensional objects,. Computer Graphics and Image

Google

Processing, 1980, 14, 249--270.

Google

Kaelbling, L. P. (1993). Learning in embedded systems. Cambridge, MA: MIT-Press.

Google

Kaelbling, L. P., Littman, M. L., & Moore, A. W. (1996). Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4.

Google

Katz, J. J. (1981). Language and other abstract objects. Oxford, UK: Basil Blackwell.

Google

Kohonen, T. (1995). Self-organizing maps (Vol. 30). Berlin: Springer.

Google

Kripke, S. (1972). Naming and necessity. Oxford, UK: Blackwell.

Google

Lambrecht, K. (1994). Information structure and sentence form: topic, focus, and the mental representations of discourse referents. Cambridge University Press.

Google

Landelius, T. (1997). Reinforcement learning and distributed local model synthesis. Unpublished doctoral dissertation, Link¨oping University, Link¨oping, Sweden.

Google

Lehmann, E., & D'Abrera, H. (1975). Nonparametrics. statistical methods based on ranks. San Francisco: Holden-Day Inc.

Google

Littman, M., & Boyan, J. (1993). A distributed reinforcement learning scheme for network routing. In J. Alspector, R. Goodman, &

Google

T. Brown (Eds.), Proceedings of the 1993 international workshop on applications of neural networks to telecommunications (p. 45-51). Hillsdale, NJ: Lawrence Erlbaum Associates.

Google

MacDorman, K. F. (1999). Partition nets: An efficient on-line learning algorithm. In Icar 99: Ninth international conference on advanced robotics. Tokyo.

Google

MacDorman, K. F. (2000). Proto-symbol emergence. In Proceedings of

Google

iros-2000: International conference on intelligent robots and systems. Takamatsu.

Google

MacLennan, B. (1991). Synthetic ethology: An approach to the study of communication. In C. G. Langton, C. Taylor, J. Farmer, & S. Rasmussen (Eds.), Artificial life ii (Vol. X). Addison-Wesley.

Google UIUC

Maes, P. (1989). How to do the right thing. Connection Science journal, 1 (3).

Google

Marconi, D. (1997). Lexical competence. Cambridge, MA: The MIT Press (A Bradford Book).

Google

Maynard Smith, J. (1982). Evolution and the theory of games. Cambridge, UK: Cambridge University Press.

Google

Maynard Smith, J., & Harper, D. (1995). Animal signals: Models and terminology. Journal of Theoretical Biology, 177, 305-311.

Google

McCallum, A. K. (1996). Reinforcement learning with selective perception and hidden state. Ph.D. Thesis.

Google

Michalski, R., Carbonell, J., & Mitchell, T. (1986). Machine learning: An artificial intelligence approach (Vol. 2). Los Altos, CA: Morgan Kaufmann Publishers.

Google

Michie, D., & Chambers, R. A. (1968). BOXES: An experiment in adaptive control. In D. E & M. D. (Eds.), Machine intelligence 2 (pp. 137-152). Edinburgh: Oliver and Boyd.

Google

Mitchell, T. M. (1980). The need for biases in learning generalizations (Technical Report No. CBM-TR-117). New Brunswick, New Jersey: Department of Computer Science, Rutgers University.

Google

Mitchell, T. M. (1997). Machine learning. McGraw-Hill.

Google

Moore, A. (1991). Variable resolution dynamic programming: Efficiently learning action maps in multivariate real-valued state-spaces. In L. Birnbaum & G. Collins (Eds.), Proceedings of the eighth international conference on machine learning. Morgan Kaufman.

Google

Moore, A. W., & Atkeson, C. G. (1995). The parti-game algorithm for variable resolution reinforcement learning in multidimensional statespaces. Machine Learning, 21 (3), 199-233.

Google

Nagel, T. (1974). What is it like to be a bat? Philosophical Review, 83, 435--450.

Google

Noble, J. (1998). The evolution of animal communication systems: questions of functions examined through simulation. Unpublished doctoral dissertation, University of Sussex, Sussex, UK.

Google UIUC

Oates, T., Eyler-Walker, Z., & Cohen, P. R. (1999). Using syntax to learn semantics: An experiment in language acquisition with a mobile robot (Tech. Rep. No. Technical Report 99-35). University of Massachusetts, Amherst.

Google UIUC

Oates, T., Schmill, M. D., & Cohen, P. R. (1999). Identifying qualitatively different outcomes of actions: Experiments with a mobile robot. In Working notes of the ijcai-99 workshop on robot action planning. Stockholm, Sweden.

Google

Oja, E. (1983). Subspace methods of pattern recognition. Letchworth: Research Studies Press Ltd.

Google

Oliphant, M. (1997). Formal approaches to innate and learned communication: Laying the foundation for language. Unpublished doctoral dissertation, University of California, San Diego, CA.

Google UIUC

Pollack, J. B. (1991). The induction of dynamical recognizers. Machine Learning, 7, 227--252.

Google

Pulliam, H., & Dunford, C. (1980). Programmed to learn. New York: Columbi University Press.

Google

Pullum, G. K. (1991). The great eskimo vocabulary hoax and other irreverent essays on the study of language. Chicago: The university of chicago press.

Google

Putnam, H. (1975). Mind, language and reality (Vol. 2). Cambridge: Cambridge University Press.

Google

Putnam, H. (1988). Representation and reality. Cambridge, MA: The MIT Press (A Bradford Book).

Google

Quinlan, J. R. (1990). Induction of decision trees. In J. W. Shavlik & T. G. Dietterich (Eds.), Readings in machine learning. Morgan Kaufmann. (Originally published in Machine Learning 1:81--106, 1986)

Google

Randløv, J., & Alstrøm, P. (1998). Learning to drive a bicycle using reinforcement learning and shaping. In Proc. 15th international conf. on machine learning (pp. 463--471). Morgan Kaufmann, San Francisco, CA.

Google

Rummery, G., & Niranjan, M. (1994). On-line Q-learning using connectionist systems. (Tech. Rep. No. CUED/F-INFENG/TR 166). Engineering Department, Cambridge University.

Google

Samuel, A. L. (1959). Some studies in machine learning using the game of checkers. IBM Journal of Research and Development, 3 (2), 210-229. (Reprinted in E. A. Feigenbaum and J. Feldman (Eds.) 1963, Computers and Thought, McGraw-Hill, New York)

Google

Sankoff, D., & Kruskal, J. B. (1983). Time warps, string edits and macromolecules; the theory and practice of sequence compari son. In (pp. 23--29). Addison-Wesley.

Google

Santamar'ia, J. C., Sutton, R. S., & Ram, A. (1998). Experiments with reinforcement learning in problems with continuous state and action spaces. Adaptive Behavior, 6 (2), 163-217.

Google

Sapir, E. (1949). Selected writings. Berkeley: University of California Press.

Google

Schmidhuber, J. (1991). Adaptive confidence and adaptive curiosity (Tech. Rep. No. FKI-149-91). M¨unchen: Technische Universit¨at M¨unchen.

Google

Schultz, W., Dayan, P., & Read Montague, P. (1997). A neural substrate of prediction and reward. Science, 275, 1593-1599.

Google

Schyns, P. G., Goldstone, R. L., & Thibaut, J.-P. (1998). The development of features in object concepts. Behavioral and Brain Sciences, In Press.

Google

Seyfarth, R., Cheney, D., & Marler, P. (1980). Monkey responses to three different alarm calls: Evidence of predator classification and semantic communication. Science, 210, 801-803.

Google

Shannon, C. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27, 379-423, 623-656.

Google

Shavlik, J. W., & Dietterich, T. G. (1990). Readings in machine learning. Morgan Kaufmann Publishers.

Google

Steels, L. (Ed.). (1993). The biology and technology of intelligent autonomous agents. Berlin: Springer Verlag.

Google

Steels, L. (1996a). Emergent adaptive lexicons. In P. Maes (Ed.), From animals to animats 4: Proceedings of the fourth international conference on simulating adaptive behavior. Cambridge, MA: The MIT Press.

Google UIUC

Steels, L. (1996b). Perceptually grounded meaning creation. In M. Tokoro (Ed.), Proceedings of the international conference on multi-agent systems icmas'96. Kyoto, Japan.

Google UIUC

Steels, L. (1996c). Self-organizing vocabularies. In C. Langton (Ed.), Proceedings of alife v, nara, japan.

Google UIUC

Steels, L. (1996d). The spontaneous self-organization of an adaptive language. In S. Muggleton (Ed.), Machine intelligence 15. Oxford, UK: Oxford University Press.

Google UIUC

Steels, L. (1997a). The synthetic modeling of language origins. Evolution of Communication, 1 (1), 1-34.

Google UIUC

Steels, L. (1997b). The origins of syntax in visually grounded robotic agents. In M. Pollack (Ed.), Proceedings of the 15th international joint conference on artificial intelligence. Los Angeles, CA: Morgan Kauffman Publishers.

Google UIUC

Steels, L. (1998). The origins of ontologies and communication conventions in multi-agent systems. Autonomous Agents and Multi-Agent Systems, 1, 169-194.

Google UIUC

Steels, L. (1999). The talking heads experiment. VUB Artificial Intelligence Laboratory.

Google

Steels, L., & Brooks, R. (Eds.). (1995). The artificial life route to artificial intelligence: Building embodied, situated agents. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Google UIUC

Steels, L., & Kaplan, F. (1998). Stochasticity as a source of innovation in language games. In C. Adami, R. Belew, H. Kitano, & C. Taylor (Eds.), Proceedings of artificial life vi. Los Angeles: MIT Press.

Google UIUC

Steels, L., & Kaplan, F. (1999). Bootstrapping grounded word semantics. In T. Briscoe (Ed.), Linguistic evolution through language acquisition: formal and computational models. Cambridge University Press.

Google UIUC

Steels, L., & Vogt, P. (1997). Grounding adaptive language games in robotic agents. In C. Husbands & I. Harvey (Eds.), Proceedings of the fourth european conference on artificial life. Cambridge MA and London: The MIT Press.

Google UIUC

Strogatz, S. H. (1994). Nonlinear dynamics and chaos. Reading, MA: Addison-Wesley Publishing Company.

Google

Sutton, R. S. (1988). Learning to predict by the methods of temporal differences (Tech. Rep. No. TR87-509.1). GTE Laboratories.

Google

Sutton, R. S. (1990). Reinforcement learning architectures for animats. In J.-A. Meyer & S. W. Wilson (Eds.), From Animals to Animats 1. Proceedings of the First International Conference on Simulation of Adaptive Behavior (SAB90) (pp. 288--296). Cambridge, MA: A Bradford Book. MIT Press.

Google

Sutton, R. S. (1996). Generalization in reinforcement learning: Successful examples using sparse coarse coding. Advances in Neural Information Processing Systems, 8, 1038-1044.

Google

Sutton, R. S., & Barto, A. G. (1998). Reinforcement learning: an introduction. Cambridge, MA: The MIT Press (A Bradford Book).

Google

Tani, J., & Nolfi, S. (1998). Learning to perceive the world as articulated. In R. Pfeifer, B. Blumberg, J. Meyer, & S. Wilson (Eds.), Proceedings of the fifth international conference on simulation of adaptive behavior (from animals to animats) (Vol. 5, p. 270-279). Cambridge, MA: the MIT Press.

Google

Tesauro, G. (1995). Temporal difference learning and TD-Gammon. Communications of the ACM, 38 (3), 58--68.

Google

Thorndike, E. (1911). Animal intelligence: Experimental studies. New York: MacMillan.

Google

Thrun, S. (1992). The role of exploration in learning control. In Handbook of intelligent control: Neural, fuzzy and adaptive approaches. Florence, Kentucky: Van Nostrand Reinhold.

Google

Tomita, M. (1982). Dynamic construction of finite-state automata from examples using hill-climbing. In Proceedings of the fourth annual cognitive science conference (pp. 105--108). Ann Arbor, MI.

Google

Van de Velde, W. (1995). The biology and technology of intelligent autonomous agents. In L. Steels (Ed.), (Vol. 144, p. 197-221). Berlin: Springer.

Google

van Orman Quine, W. (1975). Word and object. Cambridge, Mass.: MIT Press.

Google

Vogt, P. (1998). Perceptual grounding in robots. In A. Birk & J. Demiris (Eds.), Learning robots, proceedings of the ewlr-6, lecture notes on artificial intelligence 1545. Springer.

Google

Watkins, C. (1989). Learning from delayed rewards. Unpublished doctoral dissertation, King's College, Cambridge, UK.

Google

Weiss, G. (1999). Multiagent systems: A modern approach to distributed artificial intelligence. Cambridge, MA: MIT Press.

Google

Werner, G. M., & Dyer, M. G. (1991). Evolution of communication in artificial organisms. In C. G. Langton, C. Taylor, J. Farmer, & S. Rasmussen (Eds.), Artificial life ii (Vol. X). Addison-Wesley.

Google UIUC

Wheeler, M., & de Bourcier, P. (1995). How not to murder your neighbor: using synthetic behavioral ecology to study aggressive signaling. Adaptive behavior, 3 (3), 273-309.

Google

Williams, R. (1990). Adaptive state representations and estimation using recurrent connectionist networks. In M. W. T, S. R. S, & W. P. J. (Eds.), Neural networks for control (pp. 97--114). Cambridge, MA: MIT Press.

Google

Willshaw, D., Buneman, O., & Longuet-Higgins, H. (1969). Nonholographic associative memory. Nature, 222, 960--962.

Google

Wilson, S. W. (1990). The Animat Path to AI. In J.-A. Meyer & S. W. Wilson (Eds.), From Animals to Animats 1. Proceedings of the First International Conference on Simulation of Adaptive Behavior (SAB90) (pp. 15--21). Cambridge, MA: A Bradford Book. MIT Press. (http://prediction-dynamics.com/)

Google

Wise, R., & Rompre, P.-P. (1989). Brain dopamine and reward. Annual Review of Psychology, 40, 191-225.

Google

Wolpert, D. H., & Macready, W. G. (1995). No free lunch theorems for search (Tech. Rep. No. SFI-TR-95-02-010). Santa Fe Institute.

Google

Wrobel, S. (1991). Towards a model of grounded concept formation. In J. Mylopoulos & R. Reiter (Eds.), Proceedings of the twelft international joint conference on artificial intelligence. San Mateo, CA: Morgan Kaufmann Publishers.

Google

Yanco, H., & Stein, L. (1993). An adaptive communication protocol for cooperating mobile robots. In H. R. Meyer, J-A. & S. Wilson (Eds.), From animals to animats 2. proceedings of the second international conference on simulation of adaptive behavior (p. 478-485). Cambridge, MA: The MIT Press.

Google UIUC

Zahavi, A. (1975). Mate selection a selection for a handicap. Journal of Theoretical Biology, 53, 205-214.

Google

Zahavi, A. (1977). The cost of honesty (further remarks on the handicap principle). Journal of Theoretical Biology, 67, 603-605.

Google

Zhang, W., & Dietterich, T. G. (1996). High-performance job-shop scheduling with A time-delay TD- network. In D. S. Touretzky, M. C. Mozer, & M. E. Hasselmo (Eds.), Advances in neural information processing systems (Vol. 8, pp. 1024--1030). The MIT Press.

Google

Zwaan, R. A., & Radvansky, G. A. (1998). Situation models in language comprehension and memory. Psychological Bulletin, 123 (2), 162-185.

Google

 HOME   ::   Back to the Paper   ::   References Comments to: junwang4 you-know-at gmail.com Last update: 11/16/07