This article examines the relationship between environmental and cognitive structure. One of the key tasks for any agent interacting in the real world is the management of uncertainty; be cause of this the cognitive structures which interact with real environments, such as would be used in navigation, must effectively cope with the uncertainty inherent in a constantly changing world. Despite this uncertainty, however, real environments usually afford structure that can be effectively exploited by organisms. The article examines environmental characteristics and struc tures that enable humans to survive and thrive in a wide range of real environments. The rela tionsnip between these characteristics and structures, uncertainty, and cognitive structure is ex plored in the context of PLAN, a proposed model of human cognitive mapping, and R-PLAN, a version of PLAN that has been instantiated on an actual mobile robot. An examination of these models helps to provide insight into environmental characteristics which impact human perfor mance on tasks which require interaction with the world.
Alexander, C., Ishikawa, S., & Silverstein, M. (1977). A pattern language. New York: Oxford University Press.
2.
Asada, M., Yasuhito, F. & Tsuji, S. (1988). Representing a global map for a mobile robot with relational local maps from sensory data. Proceedings of the 9th International Conference on Pattern Recognition, 520-523.
3.
Bates E.A., & Elman, J.L. (1992). Connectionism and the study of change. (Tech. Rep. No. 9202). San Diego, California : The University of California at San Diego, The Center for Research in Language.
4.
Bonasso, R.P., Kortenkamp, D. & Miller, D.P. (1995). Experiences with an architecture for intelligent, reactive agents. Proceedings of the 1995 IJCAI Wlorkshop on Agent Theories, Architectures and Languages.
5.
Brooks, R.A. (1985). Visual map making for a mobile robot. Proceedings of the IEEE Conference on Robotics and Automation ., 824-829.
6.
Brooks, R.A. (1986). A robust layered control system for a mobile robot . IEEE Journal of Robotics and Automation, 2, 1:14-23.
7.
Brooks, R.A. (1991). Challenges for complete creature architectures , in From Animals to Animats, Proceedings of the First International Confererece on the Simulation of Adaptive Behavior, Meyer, J.-A. and Wilson, S.W. (eds.), MIT-Press.
8.
Bruner, J.S. (1957). On perceptual readiness. Pychological Review, 64, 123-152.
9.
Brunswik, E. (1956). Perception and the representative design of psychological experiments. Berkeley: University of California Press.
10.
Byrne, R.W. (1979). Memory for urban geography. Quarterly Journal of Experimental Psychology, 31 (1), 147-154.
11.
Chapman, D. (1987). Planning for conjunctive goals. Journal ofArtificial Intelligence, 32 (3), 333-377.
12.
Chown, E. (1994). Consolidation and Learning: A Connectionist Model of Human Credit Assignment. Doctoral dissertation. The University of Michigan.
13.
Chown, E., Kaplan, S. and Kortenkamp, D. (1995). Prototypes, Location and Associative Networks (PLAN): Towards a unified theory of cognitive mapping. Cognitive Science., 19, 1-52.
14.
Cimprich, B. (1993). Development of an intervention to restore attention in cancer patients. Cancer Nursing, 16, 83-92.
15.
Clark, A. (1989). Microcognition: Philosophy, cognitive science, and parallel distributed processing. The MIT Press.
16.
Connell, J.H. (1992). SSS: A hybrid architecture applied to robot navigation . Proceedings of the IEEE International Conference on Robotics and Automation, 2719-2724.
17.
Craik, K.J.W. (1943). The nature of exploration. London: Cambridge University Press.
18.
Gibson, J.J. (1966). The senses considered as perceptual systems. Boston, MA: Houghton Mifflin.
19.
Gladwin, T. (1970). East is a big bird: Navigation and logic on Puluwat Atoll, Harvard University Press.
20.
Gopal, S., Klatzky, R.L. & Smith, T.R. (1989). NAVIGATOR: A psychologically based model of environmental learning through navigation. Journal of Environmental Psychology , 9 (4), 309-31.
21.
Gopal, S. & Smith, T.R. (1990). Human wayfinding in an urban environment: A performance analysis of a computational process model. Environment and Planning, 22 (2), 169-91.
22.
Hebb, D.O. (1949). The organization of behavior. New York: Wiley.
23.
Hebb, D.O. (1963). The semiautonomous process, its nature and nurture . American Psychologist, 18, 16-27.
24.
Hebb, D.O. (1980). Essay on Mind. Hillsdale, NJ : Lawrence Erlbaum Associates.
25.
Hebb, D.O. (1982). The mechanisms of perception. In (H. A. Buchtel,ed.) The conceptual nervous system. Pergamon Press.
26.
Hirtle, S. & Jonides, J. (1985). Evidence of hierarchies in cognitive maps. Memory and Cognition, 13(2), 208-217.
27.
Holland, J.H. (1986). Escaping brittleness: The possibilities of general-purpose learning algorithms applied to parallel rule-based systems. In: R.S. Michalski, J.G. Carbonell & T.M. Mitchell, (E.ds.), Machine Learning: An artificial intelligence approach (Vol. 2). Los Altos, CA: Morgan Kaufmann.
28.
Horswill, I. (1993). Polly: A vision-based artificial agent. Proceedings of the National Conference on Artificial Intelligence (AAAI-93), 824-829.
29.
Kaelbling, L.P., Littman, M.L. & Moore, A.W. (1996). Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4, 237-285.
30.
Kaplan, R. (1993). The role of nature in the context of the workplace. Landscape and UrbanPlanning, 26, 193-201.
31.
Kaplan, S. (1973). Cognitive maps in perception and thought. In R. M. Downs and D. Stea (eds.), Image and Environment. Chicago: Aldine.
32.
Kaplan, S. & Kaplan, R. (1988). The Experience of Nature, Ann Arbor: Ulrichs.
33.
Kaplan, S. & Kaplan, R. (1989). The visual environment: Public participation in design and planning. Journal of Social Issues, 45, 59-86.
34.
Kaplan, S. & Peterson, C. (1993). Health and environment: A psychological analysis. Landscape and UrbanPlanning, 26, 17-23.
35.
Kaplan, S., Sonntag, M. & Chown, E. (1991) Tracing recurrent activity in cognitive elements (TRACE): A model of temporal dynamics in a cell assembly. ConnectionScience, 3, 179-206.
36.
Kortenkamp, D. (1993). Cognitive maps for mobile robots: A representation for mapping and navigation. Doctoral dissertation, The University of Michigan.
37.
Kortenkamp, D., Baker, L.D., & Weymouth, T. (1992). Using gateways to build a route map. IEEE/RSJ International Conference on Intelligence Robots and Systems ..
38.
Kortenkamp, D. & Chown, E. (1993). A directional spreading activation network for mobile robot navigation. From Animals to Animats 2, Proceedings of the Second International Conference on Simulation of Adaptive Behavior, Meyer, J.-A., Roitblat H. L. and Wilson, S.W. (eds.), MIT-Press.
39.
Kortenkamp, D., Chown, E., & Kaplan, S. (1996). Implementing a psychological model of cognitive mapping on a mobile robot: From theory to practice. Submitted.
Lakoff, G. (1987). Women, Fire, and Dangerous Things, Chicago, IL: The University of Chicago Press.
42.
Levenick, J.R. (1991). NAPS: A connectionist implementation of cognitive maps, ConnectionScience3, 107-126.
43.
Macphail, E. (1987). The comparative psychology of intelligence. Bebavioral andBrain Sciences, 10(4), 645-695.
44.
Mahadevan, S. & Connell, J. (1992). Automatic programming of behavior-based robots using reinforcement learning. Artificial Intelligence, 55, 311-365.
45.
O'Keefe, J. (1989). Computations that the hippocampus might perform . In Nadel, L., Cooper, L. A., Culicover, P. and Harnish, R. M. (eds.), Neural connections, mental computation. Cambridge, MA: MIT Press.
46.
O'Keefe, J. & Nadel, L. (1978). The hippocampus as a cognitive map. Oxford: Clarendon Press.
47.
O'Neill, M.J. (1990). Computer simulation of the cognitive map: A validation study. In R. I. Selby, K. H. Anthony, J. Choi, and B. Orland (eds.) Coryling of Age: Proceedings of the Twenty-first Annual Conference of the Environmental Design Research Association, Oklahoma City : EDRA.
48.
O'Neill, M.J. (1991). A biologically based model of spatial cognition and wayfinding. Journal of Environmental Psychology, 11, 299-320.
49.
Otto, I., Grandguillaume, P., Boutkhil, L., Burnod, Y. & Guigon, E. (1992). Direct and inderect cooperation between temporal and pareital networks for invariant visual recognition. Journal of Cognitive Neuroscience, 4, 35-57.
50.
Piaget, J., & Inhelder, B. (1967). The Child's Conception of Space, W.W. Norton and Company, New York.
51.
Shemyakin, F.N. (1962). General problems of orientation in space and space representations. In B.G. Anayev, editor, Psychological Science in the USSR Vol. 1., U.S. Joint Publications Research Service, Washington D.C., 186-251.
52.
Siegel, A.W., & White, S.H. (1975). The development of spatial representation of large-scale environments. In Reese, H. W. (ed.), Advances in Child Development and Behavior, Volume 10, Academic Press, New York, 1975.
53.
Smolensky, P. (1988). On the proper treatment of connectionism. Behavioral and Brain Sciences, 11, 1-74.
54.
Sonntag, M.L. (1991). Learning sequence in an associative network: A step towards cognitive structure. Doctoral dissertation. The University of Michigan.
55.
Squire, L.R. (1992). Memory and the hippocampus: A synthesis from findings with rats, monkeys and humans. Psychological Review, 99(2), 195-231.
56.
Tennessen, C.M. & Cimprich, B. (1995). Views to nature: Effects on attention. Journal of Environmental Psychology, 15, 77-85.
57.
Trullier, O., Wiener, S.I., Berthoz, A., & Meyer, J.A. (1997). Biologically based artificial navigation systems: Review and prospects. Progress in Neurobiology, 51, 483-544.
58.
Ungerleider, I.G. & Mishkin, M. (1982). Two cortical visual systems. In D.J. Ingle, M.A. Goodale , & R.J.W. Mansfield (Eds.), Analysis of visual behavior. Cambridge, MA: MIT Press.
59.
Weisman, G.D. (1981). Way-finding and the built environment: an evaluation of architectural legibility. Environment and Behavior, 13. 189ff.
60.
Yeap., W.K. (1988). Towards a computational theory of cognitive maps , Artificial Intelligence, 34, 297-360.
