Adaptability and diversity in simulated turn-taking behavior

Artificial Life

Volumn 10, Issue 4, 2004, Pages 361-378

  Iizuka, Hiroyuki ^a   Ikegami, Takashi ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

Adaptive behavior; Cognition; Diversity of behaviors; Embodiment; Turn taking

Indexed keywords

ADAPTIVE SYSTEMS; CHAOS THEORY; COMPUTER SIMULATION; DYNAMICS; GENETIC ALGORITHMS; MATHEMATICAL MODELS; MOBILE ROBOTS; RECURRENT NEURAL NETWORKS; SOFTWARE AGENTS;

ADAPTIVE BEHAVIOR; COGNITIVE BEHAVIOR; DYNAMICAL SYSTEMS; TURN TAKING BEHAVIOR;

COGNITIVE SYSTEMS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BEHAVIOR; COGNITION; COMPUTER INTERFACE; COMPUTER SIMULATION; EVOLUTION; HUMAN;

ALGORITHMS; BEHAVIOR; COGNITION; COMPUTER SIMULATION; EVOLUTION; HUMANS; NEURAL NETWORKS (COMPUTER); USER-COMPUTER INTERFACE;

EID: 4444317597     PISSN: 10645462     EISSN: None     Source Type: Journal    
DOI: 10.1162/1064546041766442     Document Type: Article

References (26)

1. Beer, R. D. (1997). The dynamics of adaptive behavior: A research program. Robotics and Autonomous Systems, 20, 257-289.
2. Beer, R. D. (2003). The dynamics of active categorical perception in an evolved model agent. Adaptive Behavior, 11(4), 209-243.
3. Braitenberg, V. (1984). Vehicles: Experiments in synthetic psychology. Cambridge, MA: MIT Press.
4. Cliff, D., & Miller, G. F. (1996). Co-evolution of pursuit and evasion II: Simulation methods and results. In Animals to Animats 4 (pp. 506-515). Cambridge, MA: MIT Press.
5. Dautenhahn, K. (1995). Getting to know each other - Artificial social intelligence for autonomous robots. Robotics and Autonomous Systems, 16, 333-356.
6. Dautenhahn, K. (1999). Embodiment and interaction in socially intelligent life-like agents. In C. L. Nehaniv (Ed.), Computation for metaphors, analogy and agents, Vol. 1562 of Springer Lecture Notes in Artificial Intelligence (pp. 102-142). New York: Springer-Verlag.
7. Di Paolo, E.A. (2000). Behavioral coordination, structural congruence and entrainment in a simulation of acoustically coupled agents. Adaptive Behavior, 8(1), 25-46.
8. Iizuka, H., & Ikegami, T. (2002). Simulating turn-taking behaviors with coupled dynamical recognizers. In R. K. Standish, M. A. Bedau & H. A. Abbass (Eds.), Proceedings of Artificial Life 8 (pp. 319-328). Cambridge, MA: MIT Press.
9. Ikegami, T., & Taiji, M. (1998). Structures of possible worlds in a game of players with internal models. Acta Polytechnica Scandinavica Mathematics and Computer Science Series, 91, 283-292.
10. Ikegami, T., & Taiji, M. (1999). Imitation and cooperation in coupled dynamical recognizers. Advances in Artificial Life (pp. 545-554 ). New York: Springer-Verlag.
11. Ikegami, T., & Morimoto, G. (2003). Chaotic itinerancy in coupled dynamical recognizers. Chaos: An Interdisciplinary Journal of Nonlinear Science, 13(3), 1133-1147.
12. Ikegami, T., & Iizuka, H. (2004). Simulated turn-taking and dynamics repertoire. In C.L. Nehaniv & K. Dautenhahn (Eds.), Imitation and social learning in robots, humans and animals: Behavioural, social and communicative dimensions. Cambridge, UK: Cambridge University Press.
13. Marocco, D., & Floreano, D. (2002). Active vision and feature selection in evolutionary behavioral systems. In J. Hallam, D. Floreano, G. Hayes, & J. Meyer (Eds.), From Animals to Animats 7 (pp. 247-255 ). Cambridge, MA: MIT Press.
14. Nadel, J., & Revel, A. (2003). How to build an imitator? In K. Dautenhahn & C.L. Nehaniv (Eds.), Proceedings of Second International Symposium on Imitation in Animals and Artifactss (AISB'03) (pp. 120-124).
15. Nehaniv, C. L. (2003). Evolvability. Special issue. BioSystems, 69, 77-81.
16. Nolfi, S., & Floreano, D. (2000). Evolutionary robotics: The biology, intelligence, and technology of self-organizing machines. Cambridge, MA: MIT Press.
17. Pfeifer, R., & Scheier, C. (1999). Understanding intelligence. Cambridge, MA: MIT Press.
18. Pollack, J.B. (1991). The induction of dynamical recognizers. Machine Learning, 7, 227-252.
19. Reynolds, C.W. (1995). Competition, co-evolution and the game of tag. In R. Brooks & P. Maes (Eds.), Artificial Life IV (pp. 59-69). Cambridge, MA: MIT Press.
20. Scassellati, B. (1999). Imitation and mechanisms of joint attention: A developmental structure for building social skills on a humanoid robot. In C.L. Nehaniv (Ed.), Computation for metaphors, analogy and agents, Vol. 1562 of Springer Lecture Notes in Artificial Intelligence (pp. 176-195). Springer-Verlag.
21. Tani, J. (1996). Model-based learning for mobile robot navigation from the dynamical systems perspective. IEEE Transactions on Systems, Man and Cybernetics Part B, Special Issue on Robot Learning, 26(3), 421-436.
22. Trevarthen, C. (1977). Descriptive analyses of infant communicative behaviour. In H. R. Schaffer (Ed.), Studies in Mother-Infant Interaction. London: Academic Press.
23. Trevarthen, C. (1993). The self born in intersubjectivity: The psychology of an infant communicating. In U. Neisser (Ed.), The perceived self (pp. 121-173). Cambridge, UK: Cambridge University Press.
24. Wagner G. P., & Altenberg, L. (1996). Complex adaptations and the evolution of evolvability. Evolution, 50(3), 967-976.
25. Walter W. G. (1950). An imitation of life. Scientific American, 182(5), 42-45.
26. Walter W. G. (1951). A machine that learns. Scientific American, 185(2),