In this chapter, the authors present an intention-based decision-making system. They exhibit a coherent combination of two Logic Programming-based implemented systems, Evolution Prospection and Intention Recognition. The Evolution Prospection system has proven to be a powerful system for decision-making, designing, and implementing several kinds of preferences and useful environment-triggering constructs. It is here enhanced with an ability to recognize intentions of other agents—an important aspect not well explored so far. The usage and usefulness of the combined system are illustrated with several extended examples in different application domains, including Moral Reasoning, Ambient Intelligence, Elder Care, and Game Theory.
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Given the crucial role and ubiquity of intentions in our everyday decision making (Bratman, 1987; Meltzoff, 2007; Roy, 2009b; Searle, 2010; Woodward, Sommerville, Gerson, Henderson, & Buresh, 2009), one would expect intentions to occupy a substantial place in any theory of action. However, in what concern perhaps the most prominent theory of action—rational choice theory (Binmore, 2009; Russell & Norvig, 2003)—which includes the theory of decision making—the attention is mainly, if not exclusively, given to actions, strategies, information, outcomes and preferences, but not to intentions (Roy, 2009a; van Hees & Roy, 2008).
This is not to say that no attention has been paid to the relationship between rational choice and intentions. Quite the contrary, a rich philosophical and Artificial Intelligence (AI) literature has developed on the relation between rationality and intentions (Bratman, 1987; Cohen & Levesque, 1990; Malle, Moses, & Baldwin, 2003; Singh, 1991; van Hees & Roy, 2008). Some philosophers, for example in (Bratman, 1987; Roy, 2009b), have been concerned with the role that intention plays in directing rational decision making and guiding future actions. In addition, many agent researchers have recognized the importance of intentions in developing useful agent theories, architectures, and languages, such as Rao and Georgeff with their BDI model (Rao & Georgeff, 1991, 1995), which has led to the commercialization of several high-level agent languages, e.g. in (Burmeister, Arnold, Copaciu, & Rimassa, 2008; Wooldridge, 2000, 2002). However, to the best of our knowledge, there has been no real attempt to model and implement the role of intentions in decision making, within a rational choice framework. Intentions of other relevant agents are always assumed to be given as the input of a decision making process; no system that integrates a real intention recognition system into a decision making system has been implemented so far.