This volume contains the papers presented at the 22nd International FLAIRS Conference (FLAIRS-22) held 19-21 May 2009 on Sanibel Island, Florida, USA. The call for papers attracted 158 paper submissions, 40 to the general conference and 118 to the 10 special tracks. Over 80 percent of the papers were reviewed by at least four reviewers, and all papers by at least three. Reviewing was coordinated by the program committees of the general conference and the special tracks. The program committees finally accepted the 85 papers that appear in these proceedings, all as presented papers (21 from the general conference and 64 from the special tracks) and 29 as poster papers (6 from the general conference and 23 from the special tracks).

A reinforcement learning agent involved in life-long learning in a complex and dynamic environment has to have the ability to utilize control knowledge acquired in one situation in novel contexts. As part of this, it is important for the learning agent not only to be able to learn a new skill for a specific instance of a task but also to identify similar tasks, form a reusable skill and representational abstractions for the corresponding ''task type'', and to apply these abstractions in new, previously unseen contexts. This paper presents a new approach to policy generalization that derives an abstract policy for a set of similar tasks (a ''task type'') by constructing a partial policy homomorphism from a set of basic policies learned for previously seen task instances. The resulting generalized policy can then be applied in new contexts to address new instances of similar tasks. As opposed to many recent approaches in lifelong learning systems, this approach allows to identify similar tasks based on the functional characteristics of the corresponding skills and provides a means of transferring the learned knowledge to new situations without the need for complete knowledge of the state space and the system dynamics in the new environment. To illustrate the new policy generalization method and to demonstrate its ability to reuse the gained knowledge in new contexts, it is applied to a set of grid world examples.

The purpose of this study is to evaluate the validity of measuring grammatical diversity with a specifically designed Lexical Diversity Assessment Tool (LDAT). A secondary objective is to use LDAT to determine if the level of difficulty assigned to English as a Second Language (ESL) texts corresponds to increases in grammatical, lexical, and temporal diversity. Other methods of lexical diversity assessment, such as type-token ratio (TTR), have been used with varying accuracy in an effort to determine the complexity or level of texts. We analyzed 120 ESL texts independently assigned by their sources to one of four levels (Beginner, Lower-intermediate, Upper-intermediate, and Advanced). We demonstrated that LDAT significantly reflected the grammatical diversity within these texts. While the findings conflicted with the prediction that grammatical and lexical diversity would increase with assigned level, we concluded that the implementation of LDAT in text design could provide reliable assessments of grammatical diversity.

In this paper, we examine Robot Defense, a computer game that serves as a pedagogical platform for students to explore methods typically covered in an Introductory Artificial Intelligence course. Robot Defense is the synergistic outcome of two NSF funded Course, Curriculum, and Laboratory Improvement (CCLI) projects and was first presented in (Wallace, Russell and Markov 2008). The primary contribution of this paper is to discuss the implementation of the Robot Defense platform and the outcome of its first use in the classroom.

Two sentences are paraphrases if their meanings are equivalent but their words and syntax are different. Paraphrasing can be used to aid comprehension, stimulate prior knowledge, and assist in writing skills development. While automated paraphrase assessment is both common-place and useful, research has centered solely on artificial, edited paraphrases and has used only binary dimensions (i.e., is or is-not a paraphrase). In this study, we use 1998 natural paraphrases generated by high school students that have been assessed along 10 dimensions of paraphrase (e.g., semantic completeness). This study investigates the components of paraphrase quality emerging from these dimensions, and examines whether computational approaches (e.g. LSA, MED) can simulate those human evaluations. The results suggest that semantic and syntactic evaluations are the primary components of paraphrase quality, and that computationally light systems such as LSA (semantics) and MED (syntax) present promising approaches to simulating human evaluations of paraphrases.

Researchers in the field of intelligent tutoring systems (ITS) seek to create computerized tutors that can rival the learning gains produced by human tutoring, the most effective form of instruction known. The goal of the researchers is to produce ITS that provide flexible, efficient, individualized instruction to every student. Pursuit of this common goal has led them to examine many different aspects of how students learn from tutors, how human tutors interact with their students, and how students learn in collaborative environments. Insights from those studies have informed further research into ways that computer systems can detect and respond to student knowledge gaps, misconceptions, affective states and other attributes. This research has produced important work in student modeling, knowledge representation, dialog systems, and authoring tools for efficiently creating ITS in new domains.

List of officers of the FLAIRS society.

The education community is moving towards constructed or free-text responses and computer-based assessment. At the same time, progress in natural language processing and knowledge representation has made it possible to consider free-text or constructed responses without having to fully understand the text. c-rater is a technology at Educational Testing Service (ETS) used for automatic content scoring for short, free-text responses. This paper describes some of the major developments made in c-rater recently.

This paper presents the current state of a work in progress, whose objective is to better understand the effects of factors that significantly influence the performance of Latent Semantic Analysis (LSA). A difficult task, which consists in answering (French) biology Multiple Choice Questions, is used to test the semantic properties of the truncated singular space and to study the relative influence of main parameters. A dedicated software has been designed to fine tune the LSA semantic space for the Multiple Choice Questions task. With optimal parameters, the performances of our simple model are quite surprisingly equal or superior to those of 7th and 8th grades students. This indicates that semantic spaces were quite good despite their low dimensions and the small sizes of training data sets. Besides, we present an original entropy global weighting of answers' terms of each question of the Multiple Choice Questions which was necessary to achieve the model's success.

Wikipedia is a goldmine of information; not just for its many readers, but also for the growing community of researchers who recognize it as a resource of exceptional scale and utility. It represents a vast investment of manual effort and judgment: a huge, constantly evolving tapestry of concepts and relations that is being applied to a host of tasks. This article provides a comprehensive description of this work. It focuses on research that extracts and makes use of the concepts, relations, facts and descriptions found in Wikipedia, and organizes the work into four broad categories: applying Wikipedia to natural language processing; using it to facilitate information retrieval and information extraction; and as a resource for ontology building. The article addresses how Wikipedia is being used as is, how it is being improved and adapted, and how it is being combined with other structures to create entirely new resources. We identify the research groups and individuals involved, and how their work has developed in the last few years. We provide a comprehensive list of the open-source software they have produced.