Active Object Localization in Visual Situations

We describe a method for performing active localization of objects in instances of visual situations. A visual situation is an abstract concept---e.g., "a boxing match", "a birthday party", "walking the dog", "waiting for a bus"---whose image instantiations are linked more by their common spatial and semantic structure than by low-level visual similarity. Our system combines given and learned knowledge of the structure of a particular situation, and adapts that knowledge to a new situation instance as it actively searches for objects. More specifically, the system learns a set of probability distributions describing spatial and other relationships among relevant objects. The system uses those distributions to iteratively sample object proposals on a test image, but also continually uses information from those object proposals to adaptively modify the distributions based on what the system has detected. We test our approach's ability to efficiently localize objects, using a situation-specific image dataset created by our group. We compare the results with several baselines and variations on our method, and demonstrate the strong benefit of using situation knowledge and active context-driven localization. Finally, we contrast our method with several other approaches that use context as well as active search for object localization in images.Comment: 14 page

Universal Learning of Repeated Matrix Games

We study and compare the learning dynamics of two universal learning algorithms, one based on Bayesian learning and the other on prediction with expert advice. Both approaches have strong asymptotic performance guarantees. When confronted with the task of finding good long-term strategies in repeated 2x2 matrix games, they behave quite differently.Comment: 16 LaTeX pages, 8 eps figure

Information and Beliefs in a Repeated Normal-Form Game

We study beliefs and choices in a repeated normal-form game. In addition to a baseline treatment with common knowledge of the game structure and feedback about choices in the previous period, we run treatments (i) without feedback about previous play, (ii) with no information about the opponent’s payoffs and (iii) with random matching. Using Stahl and Wilson’s (1995) model of limited strategic reasoning, we classify behavior with regard to its strategic sophistication and consider its development over time. We use belief statements to check for the consistency of subjects’ actions with the stated beliefs as well as for the accuracy of their beliefs (relative to the opponent’s true choice). In the baseline treatment we observe more sophisticated play as well as more accurate beliefs and more best responses to beliefs over time. We isolate feedback as the main driving force of learning to play strategically and to form beliefs that accurately predict the behavior of the opponent.beliefs, experiments, strategic uncertainty, learning

Learning spillover and analogy-based expectations: a multi-game experiment

We consider a multi-game interactive learning environment and ask ourselves whether long run behaviors in one game are a¤ected by behaviors in the other, i.e whether there are learning spillovers. Our main �nding is that learning spillovers arise whenever the feedback provided to subjects about past play is not easily accessible game by game and thus subjects get a more immediate impression about aggregate distributions. In such a case, long run behaviors stabilize to an analogy-based expectation equilibrium (Jehiel 2005), thereby suggesting how one should broaden the notion of equilibrium to cope with learning spillovers

Information and Beliefs in a Repeated Normal-form Game

We study beliefs and choices in a repeated normal-form game. In addition to a baseline treatment with common knowledge of the game structure, feedback about choices in the previous period and random matching, we run treatments (i) with fixed matching, (ii) without information about the opponent’s payoffs, and (iii) without feedback about previous play. Using Stahl and Wilson’s (1995) model of limited strategic reasoning, we classify behavior with regard to its strategic sophistication and consider its development over time. In the treatments with feedback and full information about the game, we observe more strategic play, more best-responses to beliefs and more accurate beliefs over time. While feedback is the main driving force of learning to play strategically and for forming beliefs that accurately predict the behavior of the opponent, both incomplete information about the opponent’s payoffs or lack of feedback lead to a stagnation of best-response rates over time. ZUSAMMENFASSUNG - (Information und Erwartungen in einem wiederholten Normalformspiel) Wir untersuchen die Entwicklung von den Erwartungen über das Verhalten des anderen Spielers und den Entscheidungen in einem wiederholten Normalformspiel. Zusätzlich zum Haupttreatment mit common knowledge über das Spiel, Feedback über das Ergebnis in der vorigen Runde und zufälliger Zuordnung der Spieler, gibt es Kontrolltreatments mit (i) festen paarweisen Zuordnungen der Spieler, (ii) ohne Information über die Auszahlungen des anderen Spielers und (iii) ohne Feedback über das Ergebnis der vorigen Runde. Mit Hilfe von Stahl und Wilsons (1995) Modell begrenzten strategischen Verhaltens klassifizieren wir das Verhalten der Teilnehmer im Hinblick auf die strategische Sophistikation. In den Treatments mit Feedback und vollständiger Information über das Spiel nehmen strategisches Verhalten, beste Antworten auf die eigenen Erwartungen und die Akkuratheit der Erwartungen über die Zeit zu. Während Feedback der Hauptgrund dafür ist, dass die Teilnehmer lernen, sich strategisch zu verhalten und korrekte Erwartungen über das Verhalten des anderen Spielers zu bilden, führen sowohl unvollständige Information über die Auszahlungen des Gegenspielers als auch fehlendes Feedback zu einer Stagnation der Rate der besten Antworten über die Zeit.

Measuring the competence-quality of vocational teachers: An advocatory approach

Using a sample of 110 persons, this study examined the ”advocatory approach” for predicting the quality of (VET) teacher’s competency profiles. The participants (teachers, experts, non-teachers) observed a concrete teaching behavior using a film vignette, and judged it by means of different quality criteria. The hypothesis that differences in the groups, who evaluate, elicit differing sensitivity about the quality of specified teaching competencies (and not teaching performance) was mostly confirmed. We suggest that teachers can individually compare their values with expert values and non-teacher values, and thus use the discrepancies in quality sensitivity for the purposes of self-guided in-service training. (DIPF/Orig.