Abstract
Emergence of responsible behavior is explored in non-cooperative games involving autonomous agents. Rather than imposing constraints or external reinforcements, agents are endowed with an elastic "sense of self" or an elastic identity that they curate based on rational considerations. This approach is called "computational transcendence (CT)." We show that agents using this model make choices for collective welfare instead of individual benefit. First, relevance of this model in game theoretic contexts like Prisoners' dilemma and collusion is presented. Next, a generic multi-agent framework for simulating dilemmas around responsible agency is also proposed. CT implemented on this framework, is shown to be versatile in acting responsibly to different kinds of circumstances-including modifying their strategy based on their interaction with other agents in the system as well as interacting with adversaries that are rational maximizers, and who have a rationale to exploit responsible behavior from other agents. CT is also shown to outperform reciprocity as a strategy for responsible autonomy. Thus, we present CT as a framework for building autonomous agents which can intrinsically act responsibly in multi-agent systems. The core model for computational ethics presented in this paper can potentially be adapted to the needs of applications in areas like supply chains, traffic management, and autonomous vehicles. This paper hopes to motivate further research on responsible AI, by exploring computational modeling of this elusive concept called the "sense of self" that is a central element of existential inquiry in humans.