It is still unclear what metacognition is. Two main theories about metacognition are reviewed, each of which claims to provide a better explanation of the phenomenon, while discrediting the other theory as inappropriate. My claim is that in order to do justice to the complex phenomenon of metacognition, we must distinguish two levels of this capacity. It can be shown that each of these theories has been trying to explain only one of the two levels and that, consequently, the conflict between them can be dissolved. Finally, I characterize each level and explain some of their interactions.

Solving real-world problems using symbolic planning often requires a simplified formulation of the original problem, since certain subproblems cannot be represented at all or only in a way leading to inefficiency. For example, manipulation planning may appear as a subproblem in a robotic planning context or a packing problem can be part of a logistics task. In this paper we propose an extension of PDDL for specifying semantic attachments. This allows the evaluation of grounded predicates, the change of fluents and the calculation of durations by externally specified functions. Furthermore, we describe a general schema of integrating semantic attachments into forward-chaining planning systems and report on our experience of adding this extension to the planner Temporal Fast Downward. Finally, we present some preliminary experiments using semantic attachments.

One approach to combining ASP and CP is to integrate There are several approaches to representing and solving theory-specific predicates into propositional formulas (motivated constraint satisfaction problems: constraint programming by SMT), and to extend the ASP solver's decision (CP; Dechter 2003, Rossi, van Beek, and Walsh 2006), answer engine with a higher level proof procedure (Baselice, set programming (ASP; Baral 2003), propositional satisfiability Bonatti, and Gelfond 2005; Mellarkod and Gelfond 2008; checking (SAT; Biere et al. 2009), its extension Gebser, Ostrowski, and Schaub 2009). However, the resulting to satisfiability modulo theories (SMT; Nieuwenhuis, Oliveras, systems have a number of limitations. First, they are and Tinelli 2006), and many more. Each has its particular tied to particular ASP and CP solvers. Second, the support strengths: for example, CP systems support global constraints, for global constraints is limited. Third, communication between ASP systems permit recursive definitions and offer the ASP and CP solver is restricted. Alternative techniques, default negation, whilst SAT solvers often exploit very such as reformulating constraints into ASP have received efficient implementations.

The most common solution concept for a strategic interaction situation is the Nash equilibrium, in which no agent can do better by deviating unilaterally. However, the Nash equilibrium underlays on the assumption of common information that is hardly verified in many practical situations. When information is not common, rational agents are assumed to learn from their observations to derive beliefs over their opponents' play and payoffs. In these situations, there are steady states composed of beliefs and strategies in which the strategies do not constitute a Nash equilibrium. These stable states are called in the game theory literature self-confirming equilibria. They are such that every agent plays the best response to her beliefs and these are correct on the equilibrium path, while off the equilibrium path they may be incorrect. We present some mathematical programming formulations for computing self-confirming equilibria and its refinements in two-player extensive-form games and we study their properties.

Early detection of cognitive impairment can prevent or delay the progress of cognitive dysfunction. In the field of neurology, the Clock Drawing Test (CDT) is one of the most popular instruments for detecting cognitive impairment. This paper presents the development of the ClockReader system, a computerized Clock Drawing Test. The main function of the system is to automate error handling in handwriting recognition. Since the ClockReader is a screening tool for dementia, it is not desirable to ask the users to fix their input errors in the drawing of either numbers or characters. Therefore, we propose a simple machine learning technique, context-bounded refinement filter algorithm. With trial experiments, we prove that this simple algorithm improves the recognizer accuracy of handwriting in clock drawings up to 88%.

Based on a typology of five basic forms of abduction, I propose a new definition of abductive insight that empha sizes in particular the inferential structure of a belief system that is able to explain a phenomenon after a new, abductive ly created component has been added to this system or the entire system has been abductively restructured. My thesis is, first, that the argumentative structure of the pursued problem solution guides abductive creativity and, second, that diagrammatic reasoning—if conceptualized according to the requirements defined by Charles Peirce—can support this guidance. This support is mainly possible based on the normative power of the system of representation that has to be used to construct diagrams and to perform experiments with them.

Tactile maps offer access to spatial-analog information for visually impaired people. In contrast to visual maps, a tactile map has a lower resolution and can only be inspected in a sequential way, complicating the extraction of spatial relations among distant map entities. Verbal assistance can help to overcome these difficulties by substituting textual labels with verbal descriptions and offering propositional knowledge about spatial relations. Like visual maps, tactile maps are based on visual, spatial-geometric representations that need to be reasoned about in order to generate verbal assistance. We present an approach towards a verbally assisting virtual-environment tactile map (VAVETaM) realized on a computer system utilizing a haptic force-feedback device. In particular, we discuss the tasks of understanding the user's map exploration procedures (MEPs), of exploiting the spatial-analog map to anticipate the user's informational needs, of reasoning about optimal assistance by taking assumed prior knowledge of the user into account, and of generating appropriate verbal instructions and descriptions to augment the map.

Until recently, the AI and in particular the NLP community GA, immediately preceding the Twenty-Fourth AAAI Conference have relied on resources built manually by experts in on Artificial Intelligence -- AAAI 2010. It is a successor specific areas (in particular linguists, philosophers, cognitive to the workshops organized at AAAI 2008 entitled linguists). User contributed knowledge has opened up "Wikipedia and Artificial Intelligence: An Evolving Synergy" a new perspective, in that it captures the kind of knowledge (WikiAI 08) and at IJCAI 2009 entitled "User Contributed and organization that arises naturally out of the consensus Knowledge and Artificial Intelligence: An Evolving of the masses, and as such represents better our collective Synergy" (WikiAI 09). The outcome is a multifaceted and extremely This volume contains papers accepted for presentation at rich source of information, revealed through embedded annotations the workshop. We issued calls for regular papers, short latebreaking and structural information.

Constraint satisfaction problems are mathematical models of real-world problems. In contrast to randomly generated artificial problems, real-world problems usually have non-random structure. Knowledge about that structure, when identified in advance, can make search to find solutions more effective. This paper introduces DrawCSP, a visualization program that can show both the original and the discovered structure of constraint satisfaction problems. DrawCSP provides insight into both search algorithm design and into the challenges real-world problems present.

Mixed reality is an important classroom tool for managing complexity from both the students' and instructor's standpoints. It can be used to provide important scaffolds when introducing robotics, by allowing elements of perception and control to be abstracted, and these abstractions removed as a course progresses (or left in place to introduce robotics to younger groups of students). In prior work, we have illustrated the potential of this approach both in providing scaffolding, building an inexpensive robotics laboratory, and also providing control of evaluation of robotics environments for student evaluation and scientific experimentation. In this paper, we explore integrating extensions and improvements to the mixed reality components themselves as part of a course in applied artificial intelligence and robotics. We present a set of assignments that in addition to exploring robotics concepts, actively integrate creating or improving mixed reality components. We find that this approach better leverages the advantages brought about by mixed reality in terms of student motivation, and also provides some very useful software engineering experience to the students.