Focusing in Dialog

Engineering and Applied Science

Establishing Context in Task-Oriented Dialogs

This paper describes part of the discourse component of a speech understanding system for task-oriented dialogs, specifically, a mechanism for establishing a focus of attention to aid in identifying the referents of definite noun phrases.Engineering and Applied Science

The Dynamics of Intentions in Collaborative Intentionality

An adequate formulation of collective intentionality is crucial for understanding group activity and for modeling the mental state of participants in such activities. Although work on collective intentionality in philosophy, artificial intelligence, and cognitive science has many points of agreement, several key issues remain under debate. This paper argues that the dynamics of intention – in particular, the inter-related processes of plan-related group decision making and intention updating – play crucial roles in an explanation of collective intentionality. Furthermore, it is in these dynamic aspects that coordinated group activity differs most from individual activity. The paper specifies a model of the dynamics of agent intentions in the context of collaborative activity. Its integrated treatment of group decision making and coordinated updating of group-related intentions fills an important gap in prior accounts of collective intentionality, thus helping to resolve a long-standing debate about the nature of intentions in group activity. The paper also defines an architecture for collaboration-capable computer agents that satisfies the constraints of the model and is a natural extension of the standard architecture for resource-bounded agents operating as individuals. The new architecture is both more principled and more complete than prior architectures for collaborative multi-agent systems.Engineering and Applied Science

Timing Interruptions for Better Human-Computer Coordinated Planning

The high operations tempo and growing complexity of planning (and re-planning) in various mission-critical domains suggest an approach in which systems act as primary planners rather than assisting the user in planning. We present a high-level overview of our design of a Coordination Autonomy (CA) module as part of such planning system, responsible to intelligently initiate and manage the necessary interactions with the user for enhancing the system's performance.Engineering and Applied Science

Sharing Experiences to Learn User Characteristics in Dynamic Environments with Sparse Data

This paper investigates the problem of estimating the value of probabilistic parameters needed for decision making in environments in which an agent, operating within a multi-agent system, has no a priori information about the structure of the distribution of parameter values. The agent must be able to produce estimations even when it may have made only a small number of direct observations, and thus it must be able to operate with sparse data. The paper describes a mechanism that enables the agent to significantly improve its estimation by augmenting its direct observations with those obtained by other agents with which it is coordinating. To avoid undesirable bias in relatively heterogeneous environments while effectively using relevant data to improve its estimations, the mechanism weighs the contributions of other agents' observations based on a real-time estimation of the level of similarity between each of these agents and itself. The "coordination autonomy" module of a coordination-manager system provided an empirical setting for evaluation. Simulation-based evaluations demonstrated that the proposed mechanism outperforms estimations based exclusively on an agent's own observations as well as estimations based on an unweighted aggregate of all other agents' observations.Engineering and Applied Science

Estimating Information Value in Collaborative Multi-Agent Planning Systems

This paper addresses the problem of identifying the value of information held by a teammate on a distributed, multi-agent team. It focuses on a distributed scheduling task in which computer agents support people who are carrying out complex tasks in a dynamic environment. The paper presents a decision-theoretic algorithm for determining the value of information that is potentially relevant to schedule revisions, but is directly available only to the person and not the computer agent. The design of a "coordination autonomy" (CA) module within a coordination-manager system provided the empirical setting for this work. By design, the CA module depends on an external scheduler module to determine the specific effect of additional information on overall system performance. The paper describes two methods for reducing the number of queries the CA issues to the scheduler, enabling it to satisfy computational resource constraints placed on it. Experimental results indicate the algorithm improves system performance and establish the exceptional efficiency---measured in terms of the number of queries required for estimating the value of information---that can be achieved by the query-reducing methods.Engineering and Applied Science

Socially Conscious Decision Making

For individually motivated agents to work collaboratively to satisfy shared goals, they must make decisions about actions and intentions that take into account their commitments to group activities. This paper examines the role of social consciousness in the process of reconciling intentions to do group-related actions with other, conflicting intentions. We operationalize the notion of social consciousness and provide a first attempt to formally add social consciousness to a cooperative decision-making model. We define a measure of social consciousness; describe its incorporation into the SPIRE experimental system, a simulation environment that allows the process of intention reconciliation in team contexts to be studied; and present results of several experiments that investigate the interaction in decision-making of measures of group and individual good. In particular, we investigate the effect of varying levels of social consciousness on the utility of the group and the individuals it comprises. A key finding is that an intermediate level of social consciousness yields better results in certain circumstances than an extreme commitment. We suggest preliminary principles for designers of collaborative agents based on the results.Engineering and Applied Science

Collaborative Plans for Complex Group Action

The original formulation of SharedPlans by B. Grosz and C. Sidner (1990) was developed to provide a model of collaborative planning in which it was not necessary for one agent to have intentions-to toward an act of a different agent. Unlike other contemporaneous approaches (J.R. Searle, 1990), this formulation provided for two agents to coordinate their activities without introducing any notion of irreducible joint intentions. However, it only treated activities that directly decomposed into single-agent actions, did not address the need for agents to commit to their joint activity, and did not adequately deal with agents having only partial knowledge of the way in which to perform an action. This paper provides a revised and expanded version of SharedPlans that addresses these shortcomings. It also reformulates Pollack's (1990) definition of individual plans to handle cases in which a single agent has only partial knowledge; this reformulation meshes with the definition of SharedPlans. The new definitions also allow for contracting out certain actions. The formalization that results has the features required by Bratman's (1992) account of shared cooperative activity and is more general than alternative accounts (H. Levesque et al., 1990; E. Sonenberg et al., 1992).Engineering and Applied Science

Applying MDP Approaches for Estimating Outcome of Interaction in Collaborative Human-Computer Settings

This paper investigates the problem of determining when a computer agent should interrupt a person with whom it is working collaboratively as part of a distributed, multi-agent team, which is operating in environments in which conditions may be rapidly changing, actions occur at a fast pace, and decisions must be made within tightly constrained time frames. An interruption would enable the agent to obtain information useful for performing its role in the team task, but the person will incur a cost in responding. The paper presents a formalization of interruptions as multi-agent decision making. It defines a novel, efficient approximation method that decouples the multi-agent decision model into separate MDPs, thereby overcoming the complexity of finding optimal solutions of the Dec-POMDP model. For single-shot situations, the separate outcomes can be combined to give an exact value for the interruption. In more general settings, the closeness of the approximation to the optimal solution depends on the structure of the problem. The paper describes domain specific heuristic functions that improve the efficiency of the approximation further for a specific application.Engineering and Applied Science