James F. Allen

Towards a general theory of action and time

Abstract A formalism for reasoning about actions is proposed that is based on a temporal logic. It allows a much wider range of actions to be described than with previous approaches such as the situation calculus. This formalism is then used to characterize the different types of events, processes, actions, and properties that can be described in simple English sentences. In addressing this problem, we consider actions that involve non-activity as well as actions that can only be defined in terms of the beliefs and intentions of the actors. Finally, a framework for planning in a dynamic world with external events and multiple agents is suggested.

Actions and Events in Interval Temporal Logic

We present a representation of events and action based on interval temporal logic that is significantly more expressive and more natural than most previous AI approaches. The representation is motivated by work in natural language semantics and discourse, temporal logic, and AI planning and plan recognition. The formal basis of the representation is presented in detail, from the axiomatization of time periods to the relationship between actions and events and their effects. The power of the representation is illustrated by applying it to the axiomatization and solution of several standard problems from the AI literature on action and change. An approach to the frame problem based on explanation closure is shown to be both powerful and natural when combined with our representational framework. We also discuss features of the logic that are beyond the scope of many traditional representations, and describe our approach to difficult problems such as external events and simultaneous actions.

A Plan Recognition Model for Subdialogues in Conversations

Previous plon-based models of dialogue understanding hove been unoble to occount for mony types of subdiologues present in noturolly occurring conversotions. One reason for this is that the models hove not clearly differentiated between the voroius woys thot on utterance con relote to a plan structure representing o topic. In this poper we present a plon-bosed theory that allows o wide variety of utterance-plan relotionships. We introduce a set of discourse plans, each one corresponding to o porticulor way that on utteronce con relote to o discourse topic, and distinguish such plans from the set of plans that ore octuolly used to model the topics. By incorporating knowledge obout discourse into o plon-bosed fromework. we con account for a wide variety of subdiologues while maintaining the computotionol odvontoges of the plon-bosed opprooch.

Toward Conversational Human-Computer Interaction

The belief that humans will be able to interact with computers in conversational speech has long been a favorite subject in science fiction, reflecting the persistent belief that spoken dialogue would be the most natural and powerful user interface to computers. With recent improvements in computer technology and in speech and language processing, such systems are starting to appear feasible. There are significant technical problems that still need to be solved before speech-driven interfaces become truly conversational. This article describes the results of a 10-year effort building robust spoken dialogue systems at the University of Rochester.

The TRAINS Project: A Case Study in Defining a Conversational Planning Agent

The TRAINS project is an effort to build a conversationally proficient planning assistant. A key part of the project is the construction of the TRAINS system, which provides the research platform for a wide range of issues in natural language understanding, mixed-initiative planning systems, and representing and reasoning about time, actions and events. Four years have now passed since the beginning of the project. Each year we have produced a demonstration system that focused on a dialog that illustrates particular aspects of our research. The commitment to building complete integrated systems is a significant overhead on the research, but we feel it is essential to guarantee that the results constitute real progress in the field. This paper describes the goals of the project, and our experience with the effort so far. .pp This paper is to appear in the Journal of Experimental and Theoretical AI, 1995.

Time and Time Again: The Many Ways to Represent Time

One of the most crucial problems in any computer system that involves representing the world is the representation of time. This includes applications such as databases, simulation, expert systems, and applications of Artificial Intelligence in general. In this brief article, I will give a survey of the basic techniques available for representing time, and then talk about temporal reasoning in a general setting as needed in AI applications. Quite different representations of time are usable depending on the assumptions that can be made about the temporal information to be represented. the most crucial issue is the degree of certainty one can assume. Can one assume that a timestamp can be assigned to each event, or barring that, that the events are fully ordered? Or can we only assume that a partial ordering of events is known? Can events be simultaneous? Can they overlap in time and yet not be simultaneous? If they are not instaneous, do we know the durations of events? Different answers to each of these questions allow very different representations of time.

An architecture for more realistic conversational systems

In this paper, we describe an architecture for conversational systems that enables human-like performance along several important dimensions. First, interpretation is incremental, multi-level, and involves both general and task- and domain-specific knowledge. Second, generation is also incremental, proceeds in parallel with interpretation, and accounts for phenomena such as turn-taking, grounding and interruptions. Finally, the overall behavior of the system in the task at hand is determined by the (incremental) results of interpretation, the persistent goals and obligations of the system, and exogenous events of which it becomes aware. As a practical matter, the architecture supports a separation of responsibilities that enhances portability to new tasks and domains.

A Robust System for Natural Spoken Dialogue

This paper describes a system that leads us to believe in the feasibility of constructing natural spoken dialogue systems in task-oriented domains. It specifically addresses the issue of robust interpretation of speech in the presence of recognition errors. Robustness is achieved by a combination of statistical error post-correction, syntactically- and semantically-driven robust parsing, and extensive use of the dialogue context. We present an evaluation of the system using time-to-completion and the quality of the final solution that suggests that most native speakers of English can use the system successfully with virtually no training.

Discourse Obligations in Dialogue Processing

We show that in modeling social interaction, particularly dialogue, the attitude of obligation can be a useful adjunct to the popularly considered attitudes of belief, goal, and intention and their mutual and shared counterparts. In particular, we show how discourse obligations can be used to account in a natural manner for the connection between a question and its answer in dialogue and how obligations can be used along with other parts of the discourse context to extend the coverage of a dialogue system.

An architecture for a generic dialogue shell

This paper describes our work on dialogue systems that can mimic human conversation, with the goal of providing intuitive access to a wide range of applications by expanding the users options in the interaction. We concentrate on practical dialogue: dialogues in which the participants need to accomplish some objective or perform some task. Two hypotheses regarding practical dialogue motivate our research. First, that the conversational competence required for practical dialogues, while still complex, is significantly simpler to achieve than general human conversational competence. And second, that within the genre of practical dialogue, the bulk of the complexity in the language interpretation and dialogue management is independent of the task being performed. If these hypotheses are true, then it should be possible to build a generic dialogue shell for practical dialogue, by which we mean the full range of components required in a dialogue system, including speech recognition, language processing, dialogue management and response planning, built in such a way as to be readily adapted to new applications by specifying the domain and task models. This paper documents our progress and what we have learned so far based on building and adapting systems in a series of different problem solving domains.