An Affective Decision Making Engine Framework for Practical Software Agents

The framework of the Affective Decision Making Engine outlined here provides a blueprint for creating software agents that emulate psychological affect when making decisions in complex and dynamic problem environments. The influence of affect on the agent's decisions is mimicked by measuring the correlation of feature values, possessed by objects and/or events in the environment, against the outcome of goals that are set for measuring the agent's overall performance. The use of correlation in the Affective Decision Making Engine provides a statistical justification for preference when prioritizing goals, particularly when it is not possible to realize all agent goals. The simplification of the agent algorithm retains the function of affect for summarizing feature-rich dynamic environments during decision making. Keywords: Affective decision making, correlative adaptation, affective agent

An Affective Decision Making Agent Architecture Using Emotion Appraisals

Interacting intelligently within a temporally dynamic environment calls for adaptive performances from artificial beings. One mechanism currently being explored to produce an intuitive-like behaviour in AI applications is that of emotion. Several popular psychological theories of emotion have been the basis for a number of agent models that are capable of synthesizing emotions. However, while these models..