Software Agents with Concerns of their Own
Luis Botelho, Luis Nunes, Ricardo Ribeiro, and Rui J. Lopes

TL;DR
This paper explores the possibility of creating software agents with intrinsic first-person meanings, enabling them to understand their actions and environment through self-observation and goal recognition.
Contribution
It introduces a novel approach for developing agents that acquire first-person meanings autonomously without pre-defined goals or capabilities.
Findings
Agents can develop first-person meanings through self-observation.
Preliminary implementations demonstrate agents understanding their actions.
Approach advances towards addressing phenomenal aspects of first-person meanings.
Abstract
We claim that it is possible to have artificial software agents for which their actions and the world they inhabit have first-person or intrinsic meanings. The first-person or intrinsic meaning of an entity to a system is defined as its relation with the system's goals and capabilities, given the properties of the environment in which it operates. Therefore, for a system to develop first-person meanings, it must see itself as a goal-directed actor, facing limitations and opportunities dictated by its own capabilities, and by the properties of the environment. The first part of the paper discusses this claim in the context of arguments against and proposals addressing the development of computer programs with first-person meanings. A set of definitions is also presented, most importantly the concepts of cold and phenomenal first-person meanings. The second part of the paper presents…
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Taxonomy
TopicsReinforcement Learning in Robotics · Multi-Agent Systems and Negotiation · Logic, Reasoning, and Knowledge
