A situated view of representation and control

@article{citeulike:267647, abstract = {Intelligent agents are systems that have a complex, ongoing interaction with an environment that is dynamic and imperfectly predictable. Agents are typically difficult to program because the correctness of a program depends on the details of how the agent is situated in its environment. In this paper, we present a methodology for the design of situated agents that is based on situated-automata theory. This approach allows designers to describe the informational content of an agent's computational states in a semantically rigorous way without requiring a commitment to conventional run-time symbolic processing. We start by outlining this situated view of representation, then show how it contributes to design methodologies for building systems that track perceptual conditions and take purposeful actions in their environments.}, author = {Rosenschein, Stanley J. and Kaelbling, Leslie P. }, citeulike-article-id = {267647}, doi = {http://dx.doi.org/10.1016/0004-3702(94)00056-7}, journal = {Artificial Intelligence}, keywords = {agent, ai, cognition, jeff, multi, situated, systems}, month = {February}, number = {1-2}, pages = {149--173}, posted-at = {2005-11-02 17:19:27}, priority = {2}, title = {A situated view of representation and control}, url = {http://dx.doi.org/10.1016/0004-3702(94)00056-7}, volume = {73}, year = {1995} }

TY - JOUR ID - citeulike:267647 L3 - citeulike-article-id:267647 TI - A situated view of representation and control JF - Artificial Intelligence VL - 73 IS - 1-2 SP - 149 EP - 173 N2 - Intelligent agents are systems that have a complex, ongoing interaction with an environment that is dynamic and imperfectly predictable. Agents are typically difficult to program because the correctness of a program depends on the details of how the agent is situated in its environment. In this paper, we present a methodology for the design of situated agents that is based on situated-automata theory. This approach allows designers to describe the informational content of an agent's computational states in a semantically rigorous way without requiring a commitment to conventional run-time symbolic processing. We start by outlining this situated view of representation, then show how it contributes to design methodologies for building systems that track perceptual conditions and take purposeful actions in their environments. KW - agent KW - ai KW - cognition KW - jeff KW - multi KW - situated KW - systems AU - Rosenschein, Stanley AU - Kaelbling, Leslie PY - 1995/02// UR - http://dx.doi.org/10.1016/0004-3702(94)00056-7 ER -