KNOWLEDGE REPRESENTATION AND REASONING KNOWLEDGE REPRESENTATION AND REASONING COGNITIVE ROBOTICS A Logical Account of Causal and Topological Maps

We consider the problem of how an agent creates a discrete spatial representation from its continuous interactions with the environment. Such represen-tation will be the minimal one that explains the ex-periences of the agent in the environment. In this paper we take the Spatial Semantic Hierarchy as the agent’s target spatial representation, and use a circumscriptive theory to specify the minimal mod-els associated with this representation. We provide a logic program to calculate the models of the pro-posed theory. We also illustrate how the different levels of the representation assume different spa-tial properties about both the environment and the actions performed by the agent. These spatial prop-erties play the role of “filters ” the agent applies in order to distinguish the different environment states it has visited.