Title :
On designing CO$T: a new approach and programming environment for distributed problem solving based on evolutionary computation and anytime algorithms
Author :
Eberbach, Eugene ; Eberbach, Eugene
Author_Institution :
Dept. of Comput. & Inf. Sci., Massachusetts Univ., North Dartmouth, MA, USA
Abstract :
In This work we present a unified view of AI inspired by ideas from evolutionary computation as design of bounded rational agents. The approach specifies optimal programs rather than optimal actions, and is based on process algebras and anytime algorithms. The search method described in This work is so general than many other search algorithms, including evolutionary search methods, become its special case. We present a practical design of the programming language and environment targeting real-time complex domains. As AI systems move into more complex domains, all problems become real-time, because the agent never have long enough time to solve the decision problem exactly.
Keywords :
distributed algorithms; evolutionary computation; large-scale systems; logic programming languages; process algebra; programming languages; real-time systems; search problems; software agents; CO$T; anytime algorithms; bounded rational agents; decision problem; distributed problem solving; evolutionary computation; evolutionary search methods; optimal programs; process algebras; programming environment; programming language; real-time complex domains; search algorithms; Algorithm design and analysis; Artificial intelligence; Computer science; Evolutionary computation; Genetic algorithms; Genetic programming; Problem-solving; Programming environments; Search methods; Turing machines;
Conference_Titel :
Evolutionary Computation, 2004. CEC2004. Congress on
Print_ISBN :
0-7803-8515-2
DOI :
10.1109/CEC.2004.1331119