Human-inspired goal reasoning implementations: A survey

Goal reasoning is the ability of an artificial system to reason over its goals; it can identify, manage, plan, and execute its goals. In complex environments where requirements could change often, goal reasoning functionality is essential. Goal reasoning agents may rely on a motivation system to guide the goal reasoning process; we refer to such agents as motivated agents. Motivated agents can be explicitly or implicitly motivated by external or internal motivations. While the bulk of goal reasoning work has focused on agents that have implicit external motivations, internal motivations may offer some unique benefits to goal reasoning. As artificial internal motivations have a natural analogue to the human motivation system, this work investigates recent advances in motivated agents, where motivations are modeled on the human integrated-self. In this survey, we review those goal reasoning systems whose meta-reasoning and other goal reasoning subprocesses are at least in part intrinsic or identified, i.e., arising from idiosyncratic factors such as identity, a value system, emotions, experiences and so forth. For each system surveyed we evaluate its goal reasoning processes according to an analysis framework. We use our findings to draw conclusions about the potential benefits the three self-system categories: motives, mental simulation, and emotion bring to the goal reasoning paradigm.

Automated summary

Goal reasoning is an essential functionality for artificial systems to manage and execute goals in complex and changing environments. This survey investigates motivated agents that simulate human integrated-self, exploring the potential benefits of internal motivations in goal reasoning. By evaluating different systems, the study concludes the potential advantages of motives, mental simulation, and emotion in the goal reasoning paradigm.