A canonical theory of dynamic decision-making

Decision-making behavior is studied in many very different fields, from medicine and eco- nomics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptual- ization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering

Artificial Cognition for Social Human-Robot Interaction: An Implementation

© 2017 The Authors Human–Robot Interaction challenges Artificial Intelligence in many regards: dynamic, partially unknown environments that were not originally designed for robots; a broad variety of situations with rich semantics to understand and interpret; physical interactions with humans that requires fine, low-latency yet socially acceptable control strategies; natural and multi-modal communication which mandates common-sense knowledge and the representation of possibly divergent mental models. This article is an attempt to characterise these challenges and to exhibit a set of key decisional issues that need to be addressed for a cognitive robot to successfully share space and tasks with a human. We identify first the needed individual and collaborative cognitive skills: geometric reasoning and situation assessment based on perspective-taking and affordance analysis; acquisition and representation of knowledge models for multiple agents (humans and robots, with their specificities); situated, natural and multi-modal dialogue; human-aware task planning; human–robot joint task achievement. The article discusses each of these abilities, presents working implementations, and shows how they combine in a coherent and original deliberative architecture for human–robot interaction. Supported by experimental results, we eventually show how explicit knowledge management, both symbolic and geometric, proves to be instrumental to richer and more natural human–robot interactions by pushing for pervasive, human-level semantics within the robot's deliberative system

What is a Good Plan? Cultural Variations in Expert Planners’ Concepts of Plan Quality

This article presents the results of a field research study examining commonalities and differences between American and British operational planners’ mental models of planning. We conducted Cultural Network Analysis (CNA) interviews with 14 experienced operational planners in the US and UK. Our results demonstrate the existence of fundamental differences between the way American and British expert planners conceive of a high quality plan. Our results revealed that the American planners’ model focused on specification of action to achieve synchronization, providing little autonomy at the level of execution, and included the belief that increasing contingencies reduces risk. The British planners’ model stressed the internal coherence of the plan, to support shared situational awareness and thereby flexibility at the level of execution. The British model also emphasized the belief that reducing the number of assumptions decreases risk. Overall, the American ideal plan serves a controlling function, whereas the British ideal plan supports an enabling function. Interestingly, both the US and UK would view the other’s ideal plan as riskier than their own. The implications of cultural models of plans and planning are described for establishing performance measures and designing systems to support multinational planning teams

An empirical study of argumentation schemes in deliberative dialogue

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