Arguments and actions: decoupling preference and planning through argumentation

© 2011 Dr. Michelle BlomAutomated decision-making and planning is a capability that lays the foundation for the development of intelligent decision-support. These systems range from sophisticated multi-agent solutions for corporate decision-support, to decision recommendation for the general consumer. The ideas, algorithms, and tools developed within this thesis cater for this latter category - a class of approaches that includes online travel planners, smart environments, context-aware navigational aides, and personal shopping assistants. Operating on behalf of a human user, these tools are charged with the recommendation of a decision that best serves their interests - characterised by their preference over available choices. The mission of an automated decision-maker is to extract and use this knowledge in the selection of a decision. Across the range of problem-domain scenarios faced by a human decision-maker, the appropriate means by which their preference is communicated varies - from the quantitative to qualitative, logical to heuristic, and simple to complex. The capacity of these tools to select choices on the basis of such wide ranging classes of preference increases their utility as human decision aides. This thesis considers the decoupling of preference from the decision-making and planning algorithms that underly such systems. These algorithms operate on this preference as if it were an instance of an abstract type - supporting the use of general expressions of preference while abstracting away from its representational detail. Such algorithms can not only be reused across a range of decision-making problems faced by an agent or user, but cater for the diversity of human users on whose behalf decision-making is taking place. This thesis presents three key contributions within this domain. The existing body of work within the field of automated decision-making and planning with preference is critiqued, identifying the field of computational argumentation as a promising vehicle for the discovery of decoupled decision-making. The argumentation-based approach to decision-making allows preference to be captured by structures - structures that are manipulated by the decision-making process as abstract entities. This thesis develops a decoupled algorithm for the selection of choices on the basis of general mechanisms of choice comparison - a feat not achieved within existing work. Attention is then shifted from decision-making over single choices or actions to the problem of planning with preference. Algorithms are developed that chart a course of action for an agent or human user to follow in pursuit of their goals. This thesis focuses on a specific planning formalism - the GOLOG family of agent programming languages. High level instructions in the form of programs are interpreted to discover a sequence of actions for an agent or human user to perform. Two interpreters are devised for the discovery of preferred program executions - the first providing support for only one form of preference expression; the second presenting a decoupled approach to program interpretation with general preference. These interpreters go beyond the capabilities of existing works, with improved heuristic guidance in the form of a relaxed lookahead and support for decoupling through argumentation-based program interpretation