Automatic Synthesis of Control Sequences: A Nonlinear Planning Approach

Luis Castillo, Juan Fdez-Olivares, Antonio Gonzalez

This paper presents an approach to the application of artificial intelligence planning techniques to the generation of control sequences for manufacturing systems. These systems have some special features that must be considered in the planning process, but usual models of action present difficulties to deal with them. Therefore, a model of action derived from the classic model of STRIPS is defined and a nonlinear planning algorithm is derived from POP, both able to deal with these features.


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