Toward a logical framework for cognitive effects-based operations: Some empirical and computational results

At present, military modeling and simulation technologies do not possess the representational expressivity needed in order to formally capture the notion of a fully functional organization. Collective, robust, purposive behavior which is typically associated with multiple human actors working in concert has been (largely) outside of the grasp of the military modeling and simulation community. In this thesis, the challenge of modeling organizational behavior will be explored in light of the Effects-based Operations (EBO) paradigm. EBO has manifested itself as a paradigmatic shift towards looking at military planning as fully understanding the causal linkages between taking action and the resultant cascading effects (both intended and unintended) which ripple through the battlespace. While a reasonable amount of research has been directed at understanding the dynamics of physical effects, relatively little attention has been paid to the psychological dimension of effects. The research presented here are the first steps toward a computational framework for a full-spectrum (physical and psychological) analysis of effects called CEBO, standing for Cognitive Effects-Based Operations. CEBO will begin to take shape through the exploration of organizations (multi-agent systems) using the machinery of deontic logic; a family of logical languages used to reason about norms. In order to establish the viability of deontic logic as a mechanism for simulating human-like organizational behavior with respect to norms, I have investigated deontic reasoning from the perspective of cognitive psychology, producing results concerning how humans may mentally represent, reason about, and take appropriate action with respect to norms. As the reasonability of deontic logic as an appropriate formalism for laying the foundations for CEBO is established, I present a computational model of socio-cognitive agency which is consistent with modern conceptions of agent-based normative reasoning, implemented using the Athena denotational proof language (DPL) [67]. Athena performs proof checking, inference; model-checking, and model-building (for counterexample generation) allowing us to reason about normative contingencies and requirements between agents within an organization. Finally, I present an extension to this formal language which allows agents to possess multiple, possibly conflicting sets of obligations, and the machinery by which they may be reasoned over.