We evaluate conversational transcripts of deceptive speech using a sophisticated natural language processing tool called Coh-Metrix. Coh-Metrix is unique in that it tracks linguistic features based on social and cognitive factors. The results from Coh-Metrix are compared to linguistic features reported in previous independent deception research, which used a natural language processing tool called LIWC. The comparison provides converging validity for several linguistic features, and establishes new insights on deceptive language.

We present a little crawling robot with a two DOF arm that learns to move forward within about 15 seconds in real time. Due to its small size and weight the robot is ideally suited for classroom demonstrations as well as for talks to the public. Students who want to practice their knowledge about reinforcement learning and value iteration can use a wireless connection to a PC and monitor the internal state of the robot such as the value function or the reward table. Due to its adaptivity, depending on the surface properties of the underground the robot may surprise its audience with unexpected but efficient walking policies. The GUI is open source and the robot hardware is available as a kit from the authors.

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.

Semi-supervised learning is an active research field. Previous results shown that unite background information into the original unsupervised clustering problem could archive higher accuracy. In this paper, we explore the cooperation between the pairwise constrains given by the user and the sematic information in natural language. In addition, we reduce the time complexity to make the algorithm feasible for large quantities of data. Experiments on different scales of corpus show the robustness and effectiveness of the proposed algorithm, which the F-measure archives 20% higher than previous algorithms.

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.

In this paper knowledge representation and inference issues for rule-based systems are discussed. The paper deals with improving the logical calculus of Set Attributive Logic founding an expressive rule language XTT2. Representation extensions are introduced, and practical inference rules provided. The original includes an extended state specification, as well as interpreter design. xamples of rule analysis are given. Visual design tool HQed assuring rule quality is also presented.

List of officers of the FLAIRS society.

Route robustness is therefore a Vehicle route planning is a popular application of AI automated measure against the risk that the solution may not be executed planning methods. In numerous applications it is according to the a priori plan. The main idea behind supported with GPS navigation. Based on a generalized the concept of a robust plan is that such a plan should consist shortest-path approach it uses a directed graph as the search of numerous alternative plans, represented in a concise way, domain and edge weights set to match the required optimality and enable switching from the plan currently being executed criteria. Moreover, various additional constraints and to a new one as often as may become necessary. The degree heuristic information can be explored. (Nau, Ghallab, and of robustness is a qualitative factor referring to numerous Traverso 2004)

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.

Many reinforcement learning exploration techniques are overly optimistic and try to explore every state. Such exploration is impossible in environments with the unlimited number of states. I propose to use simulated exploration with an optimistic model to discover promising paths for real exploration. This reduces the needs for the real exploration.