We consider the problem of representing plans for mixed-initiative planning, where several participants cooperate to develop plans. We claim that in such an environment, a crucial task is plan communication: the ability to suggest aspects of a plan, accept such suggestions from other agents, criticize plans, revise them, etc., in addition to building plans. The complexity of this interaction imposes significant new requirements on the representation of plans. We describe a formal model of plans based on defeasible argument systems that allows us to perform these types of reasoning. The arguments that are produced are explicit objects that can be used to provide a semantics for statements about plans.

We develop, analyze, and evaluate a novel, supervised, specific-to-general learner for a simple temporal logic and use the resulting algorithm to learn visual event definitions from video sequences. First, we introduce a simple, propositional, temporal, event-description language called AMA that is sufficiently expressive to represent many events yet sufficiently restrictive to support learning. We then give algorithms, along with lower and upper complexity bounds, for the subsumption and generalization problems for AMA formulas. We present a positive-examples -- only specific-to-general learning method based on these algorithms. We also present a polynomial-time -- computable "syntactic" subsumption test that implies semantic subsumption without being equivalent to it. A generalization algorithm based on syntactic subsumption can be used in place of semantic generalization to improve the asymptotic complexity of the resulting learning algorithm. Finally

This paper is about the information-theoretic foundations upon which useful explanatory and predictive models of dynamic geographic phenomena can be based. It traces the development over the last decade or so of these foundations, from sequences of temporal snapshots, through object life histories, to event chronicles. A crucial ontological distinction is drawn between “things ” and “happenings”, that is between continuant and occurrent entities. Most of the work up to now has focused on representing the evolution through time of geographic things, whether objects or fields. This paper argues that happenings should be upgraded to an equal status with things in dynamic geographic representations, and suggests ways of doing this. The main research focus of the paper is the application of an algebraic approach, previously developed mainly in the context of computational processes, to real-world happenings. It develops a pure process theory of space and time, and demonstrates its applicability by providing an example of the representation of motion of a vehicle through a region. The paper concludes by noting some of the requirements for scaling this approach to real-world dynamic scenarios, such as might be found, for example, in the automation of coordination of disaster relief.

Recognizing human interactions is a challenging task due to the multiple body parts of interacting persons and the concomitant occlusions. This paper presents a method for the recognition of twoperson interactions using a hierarchical Bayesian network (BN). The poses of simultaneously tracked body parts are estimated at the low level of the BN, and the overall body pose is estimated at the high level of the BN. The evolution of the poses of the multiple body parts are processed by a dynamic Bayesian network (DBN). The recognition of two-person interactions are expressed in terms of semantic verbal descriptions at multiple levels; individual bodypart motions at low level, single-person actions at middle level, and two-person interactions at high level. Example sequences of interacting persons illustrate the success of the proposed framework. Keywords surveillance, event recognition, scene understanding, human interaction,

We aim to define an event ontology that allows natural representation of complex spatio-temporal events common in the physical world by a composition of simpler events. The events are abstracted into three hierarchies. Primitive events are defined directly from the mobile object properties. Single-thread composite events are a number of primitive events with temporal sequencing. Multi-thread composite events are a number of single-thread events with temporal /spatial/logical relationships. This hierarchical event representation naturally leads to a language description of the events. We define an Event Recognition Language (ERL) which allows the users to define the events of interest conveniently without interacting with the low level processing in the program. We will also briefly mention some approaches to compute the proposed representation.

Explanation closure (EC) axioms were previously introduced as a means of solving the frame problem. This paper provides a thorough demonstration of the power of EC combined with action closure (AC) for reasoning about dynamic worlds, by way of Sandewall's test suite of 12-or-so problems [29-31]. Sandewall's problems range from the "Yale turkey shoot" (and variants) to the "stuffy room" problem, and were intended as a test and challenge for nonmonotonic logics of action. The EC/AC-based solutions for the most part do not resort to nonmonotonic reasoning at all, yet yield the intuitively warranted inferences in a direct, transparent fashion. While there are good reasons for ultimately employing nonmonotonic or probabilistic logics -- e.g., pervasive uncertainty and the qualification problem -- this does show that the scope of monotonic methods has been underestimated. Subsidiary purposes of the paper are to clarify the intuitive status of EC axioms in relation to action effect axioms; and to show how EC, previously formulated within the situation calculus, can be applied within the framework of a temporal logic similar to Sandewall's "discrete uent logic", with some gains in clarity.

The standard pipeline approach to semantic processing, in which sentences are morphologically and syntactically resolved to a single tree before they are interpreted, is a poor fit for applications such as natural language interfaces. This is because

this paper, the language and the axioms of Event Calculus are extended to allow representing and reasoning about hypothetical actions, performed either at the present time or in the past, altough counterfactuals are not supported. Both Event Calculus and its extension are defined as logic programs so that theories are readily adaptable for Prolog query interpretation. For a reasonably large class of theories and queries, Prolog interpretation is shown to be sound and complete w.r.t. the main semantics for logic programs.

Many real world applications require systems with both reasoning and sensing/acting capabilities. However, most often, these systems do not work properly, i.e. they fail to execute actions and rarely perceive the external world correctly. No action, even if apparently simple, is guaranteed to succeed and, therefore, no planning can be "sound" (with respect to the real world) without taking into account failure. In this paper, we present a theory of planning that provides (1) a language that allows us to express failure; (2) a declarative formal semantics for this language; (3) a logic for reasoning about (possibly failing) plans. 1 Failure Many real world applications require systems with both reasoning and sensing/acting capabilities. Reasoning allows systems to achieve high level goals. Acting and sensing allows them to work in a complex and unpredictable external environment. Most often, systems sensing and acting in the world do not work properly, i.e. they fail to exe...

This dissertation describes the formal foundations and implementation of a commonsense, mixed-initiative plan reasoning system. By "plan reasoning" I mean the complete range of cognitive tasks that people perform with plans including, for example, plan construction (planning), plan recognition, plan evaluation and comparison, and plan repair (replanning), among other things. "Mixed-initiative" means that several participants can each make contributions to the plan under development through some form of communication. "Commonsense" means that the system represents plans and their constituents at a level that is "natural" to us in the sense that they can be described and discussed in language. In addition, the reasoning that the system performs includes those conclusions that we would take to be sanctioned by common sense, including especially those conclusions that are defeasible given additional knowledge or time spent reasoning. The main theses of this dissertation are the following: ...