This article presents new algorithms for inferring users' activities in a class of flexible and open-ended educational software called exploratory learning environments (ELEs). Such settings provide a rich educational environment for students, but challenge teachers to keep track of students' progress and to assess their performance. This article presents techniques for recognizing students' activities in ELEs and visualizing these activities to students. It describes a new plan-recognition algorithm that takes into account repetition and interleaving of activities. This algorithm was evaluated empirically using two ELEs for teaching chemistry and statistics used by thousands of students in several countries.

IPC-2014 was held in three separate parts to assess the state of the art in three prominent areas of planning research: the deterministic (classical) part (IPCD), the learning part (IPCL), and the probabilistic part (IPPC). Each part evaluated planning systems in ways that pushed the edge of existing planner performance by introducing new challenges, novel tasks, or both. The competition surpassed again the number of competitors that participated in its predecessor, highlighting the competition's central role in shaping the landscape of ongoing developments in evaluating planning systems. Actions are usually expressed in terms of preconditions and effects. Preconditions indicate the requirements that must hold to apply the action, while effects are the consequence (including the cost) of applying the action to the state of the world.

Intentions in Communication is the outgrowth of an interdisciplinary workshop on the role of intention in theories of communication. Attending the workshop were researchers in computer science, linguistics, philosophy, and psychology. The resulting book contains edited versions of 14 papers (13 of which were presented at the workshop), commentaries, and an introduction. The topics of these papers range from philosophical analyses of the concept of intention to algorithms for recognizing plans, from logical formalizations of speech acts to analyses of intonational contours in discourse. The idea of relating intentions to the use of language is an outgrowth of speech act theory.

We describe the application of plan-recognition techniques to support human intelligence analysts in processing national security alerts. Our approach is designed to take the noisy results of traditional data-mining tools and exploit causal knowledge about attacks to relate activities and uncover the intent underlying them. Identifying intent enables us to both prioritize and explain alert sets to analysts in a readily digestible format. Our empirical evaluation demonstrates that the approach can handle alert sets of as many as 20 elements and can readily distinguish between false and true alarms. We discuss the important opportunities for future work that will increase the cardinality of the alert sets to the level demanded by a deployable application.

SP2.0 is a new version of the heuristic HSP2.0 can specify the state space to be The syntax for the instance and domain files is given by the PDDL standard. HSP2.0, the search can be done either forward For example, it can tell HSP2.0 to HSP2.0 ran three options concurrently for three The choice for the three-minute threshold was empirical, following the observation that the regression search most often solved problems quickly or didn't solve them at all. The states s S are collections of atoms from A. S2. The actions a A(s) are the operators op O such that Prec(op) s. The transition function f maps states s into states s′ s - Del(a) Add(a) for a A(s).

As in past years, papers were solicited in two categories: (1) deployed applications and (2) emerging applications and technologies. Deployed applications are systems that have been in use for at least several months by individuals or organizations other than their developers, have measurable benefits, and incorporate AI technologies. Emerging applications are technologies and systems that are close to deployment and clearly show an innovative implementation of AI technologies. All these case studies are of value not only to other application developers looking for guidance in applying various techniques to their own applications but also to researchers who need to understand the myriad of technical challenges provided by real-world problems. At IAAI-2001, five deployed applications and seven emerging application papers were presented.

As in past years, papers were solicited in two categories: (1) deployed applications and (2) emerging applications and technologies. Deployed application papers describe systems that have been in use for at least several months by individuals or organizations other than their developers, have measurable benefits, and incorporate AI technologies. Emerging applications are technologies and systems that are close to deployment and clearly show an innovative implementation of AI technologies. These papers are of value not only to other application developers looking for guidance in applying various techniques to their own applications but also to researchers who need to understand the unique technical challenges provided by real-world problems. For IAAI-2002, we received 54 submissions, containing a wealth of outstanding applications and emerging technology papers (15 deployed and 39 emerging).

This case study article describes the iterative design process of an AIbased mixed-initiative calendaring tool with embedded artificial intelligence. We establish the specific types of assistance in which the target user population expressed interest, and we highlight our findings regarding the scheduling practices and the reminding preferences of these users. These findings motivated the redesign and enhancement of our intelligent system. Lessons learned from the study--namely, that AI systems must be usable to gain widespread adoption and retention and that simple problems that perhaps do not necessitate complex AIbased solutions should not go unattended merely because of their inherent simplicity--conclude the article, along with a discussion of the importance of the iterative design process for any user adaptive system. We are working within the infrastructure of a general-purpose, computerized office assistant named CALO (Myers et al. 2007).

This article surveys previous work on combining planning techniques with expressive representations of knowledge in description logics to reason about tasks, plans, and goals. Description logics can reason about the logical definition of a class and automatically infer class-subclass subsumption relations as well as classify instances into classes based on their definitions. Descriptions of actions, plans, and goals can be exploited during plan generation, plan recognition, or plan evaluation. These techniques should be of interest to planning practitioners working on knowledge-rich application domains. Another emerging use of these techniques is the semantic web, where current ontology languages based on description logics need to be extended to reason about goals and capabilities for web services and agents.

This is a summary of the Workshop on Planning that was sponsored by the Defense Advanced Research Project Agency and held in Santa Cruz, California, on October 21-23, 1987. The purpose of this workshop was to identify and explore new directions for research in planning. For the purposes of this article, a planner is a program that controls one or more devices capable of carrying out actions in the real world in order to achieve some definite purpose. A strategic planner is capable of anticihe workshop was organized into five sessions. Each session was intended to examine some aspect of planning research or point directions toward future work.