Preference-based reasoning in BDI agent systems

Abstract

An important feature of BDI agent systems is number of different ways in which an agent can achieve its goals. The choice of means to achieve the goal in made by the system at run time, depending on contextual information that is not available in advance. In this article, we explore ways that the user of an agent system can specify preferences which can be incorporated into the BDI execution process and used to guide the choices made. For example, a user of a travel system can specify a preferred airline, or a particular kind of accommodation, and the system will use this information to satisfy the goal and preferences, if possible. Preferences are specified in terms of properties of goals and resource usage, and are used to make two types of decisions: (a) select a plan when there is a choice and (b) determine the order in which subgoals of a plan should be pursued when their order is not fixed by design. We have implemented our preference framework in Jadex, and provide detailed case studies within the context of a holiday travel agent application.

Towards Circular Economy implementation: an agent-based simulation approach for business model changes

“…Besides the use of cognitive approaches in ABMs [14][15][16] customer preferences can be represented by utility functions in order to make desire and preferences measurable and derive estimations about future demand. The underlying assumption is that if preferences can be represented by a utility function then demand can be concluded based on maximization of utility of a product.…”

Semantic Agent-Based Service Middleware and Simulation for Smart Cities

“…Each management agent in the middleware abides by a Belief-Desire-Intention (BDI) model [26]; a set of beliefs, desires and intentions are defined to model the behavior of the agent. At runtime, the BDI engine monitors the agent’s belief, which is the state about its managed SAs and neighbors’ SAs, together with a probability distribution.…”

Applying norms and preferences for designing flexible game rules

“…Preferences have been previously implemented in a BDI context with similar principles such as in Visser et al (2011Visser et al ( , 2016, where preferences could be specified in relation to plan properties. These properties provide more detailed information about what exactly will happen when a plan is used to achieve a goal.…”

“…Numerical plan property values are then compared to preferences to sort the plans applicable to the goal in terms of how well they suit the preference set. Visser et al (2011Visser et al ( , 2016) also deals with the upward propagation of plan properties through the tree so that any reasoning about plan properties takes into account the properties of the lower level plans which may need to be carried out in order to satisfy a plan's sub-goals. This issue is also present in our work and we propagating plan properties in a similar fashion to the method described in the paper.…”

“…We define a preference as a specified theme with a numerical weighting out of 10. This definition is a simpler version of the similar concepts in Visser et al (2011Visser et al ( , 2016 and Bienvenu et al (2006) which allow for more detailed specifications such as preferences which need only be satisfied once or until some condition has been met. In contrast, our preference system assumes that the specified preferences are applicable throughout the execution of the game.…”