Hybrid Anticipatory Networks

This paper presents a theory of hybrid anticipatory networks that generalizes earlier models of consequence anticipation in multicriteria decision problems. We assume that the decision maker takes into account the anticipated outcomes of future decision problems linked by the causal relations with the present decision problem. This can be represented by a multigraph, where decision problems are modeled as nodes linked causally and by one or more additional anticipation relations. These types of multigraphs are termed anticipatory networks. Hybrid anticipatory systems may contain additional models of random and non-cooperative game decisions. Constructive solution methods for decision problems modeled by anticipatory networks are discussed as well. Further, we present a generalization of hybrid anticipatory networks, known as superanticipatory systems. In the final section we discuss some of their applications in the design of decision-making rules in autonomous robotic systems and in filtering technology development scenarios.