The Rational Selection of Goal Operations and the Integration ofSearch Strategies with Goal-Driven Autonomy

TL;DR

This paper explores how intelligent systems can effectively select and integrate goal operations and search strategies to improve autonomous decision-making and adaptability in dynamic environments.

Contribution

It introduces a method for selecting among goal operations when multiple processes co-occur, enhancing goal-driven autonomy in embodied cognitive systems.

Findings

Improved decision-making in dynamic marine search tasks

Effective integration of search strategies with goal operations

Demonstrated benefits of the proposed method in real-world scenarios

Abstract

Intelligent physical systems as embodied cognitive systems must perform high-level reasoning while concurrently managing an underlying control architecture. The link between cognition and control must manage the problem of converting continuous values from the real world to symbolic representations (and back). To generate effective behaviors, reasoning must include a capacity to replan, acquire and update new information, detect and respond to anomalies, and perform various operations on system goals. But, these processes are not independent and need further exploration. This paper examines an agent's choices when multiple goal operations co-occur and interact, and it establishes a method of choosing between them. We demonstrate the benefits and discuss the trade offs involved with this and show positive results in a dynamic marine search task.