Extending DTGOLOG with Options
نویسندگان
چکیده
Multi-class problems have a richer structure than binary classification problems. Thus, they can potentially improve their performance by exploiting the relationship among class labels. While for the purposes of providing an automated classification result this class structure does not need to be explicitly unveiled, for human level analysis or interpretation this is valuable. We develop a multi-class large margin classifier that extracts and takes advantage of class relationships. We provide a bi-convex formulation that explicitly learns a matrix that captures these class relationships and is de-coupled from the feature weights. Our representation can take advantage of the class structure to compress the model by reducing the number of classifiers employed, maintaining high accuracy even with large compression. In addition, we present an efficient formulation in terms of speed and memory.
منابع مشابه
Decision Making in Uncertain Real-World Domains
DTGolog, a decision-theoretic agent programming language based on the situation calculus, was proposed to ease some of the computational difficulties associated with Markov Decision Processes (MDPs) by using natural ordering constraints on execution of actions. Using DTGolog, domain specific constraints on a set of policies can be expressed in a high-level program to reduce significantly comput...
متن کاملOn-Line Decision-Theoretic Golog for Unpredictable Domains
DTGolog was proposed by Boutilier et al. as an integration of decision-theoretic (DT) planning and the programming language Golog. Advantages include the ability to handle large state spaces and to limit the search space during planning with explicit programming. Soutchanski developed a version of DTGolog, where a program is executed on-line and DT planning can be applied to parts of a program ...
متن کاملDecision Making in Uncertain Real-World Domains Using DT-Golog
DTGolog, a decision-theoretic agent programming language based on the situation calculus, was proposed to ease some of the computational difficulties associated with Markov Decision Processes (MDPs) by using natural ordering constraints on execution of actions. Using DTGolog, domain specific constraints on a set of policies can be expressed in a high-level program to reduce significantly comput...
متن کاملDecision-Theoretic GOLOG with Qualitative Preferences
Personalization is becoming increasingly important in agent programming, particularly as it relates to the Web. We propose to develop underspecified, task-specific agent programs, and to automatically personalize them to the preferences of individual users. To this end, we propose a framework for agent programming that integrates rich, nonMarkovian, qualitative user preferences expressed in a l...
متن کامل