toward memory-based reasoning - Computer Science, Columbia
... similarity-based induction, seeks to make decisions by "remembering" similar circumstances in the past. This is done by counting c6mbinations of features, . 5 This is the complicated part of the algorithm. In general, a particular diagno sis will correspond to a range of values for a predictor. If ...
... similarity-based induction, seeks to make decisions by "remembering" similar circumstances in the past. This is done by counting c6mbinations of features, . 5 This is the complicated part of the algorithm. In general, a particular diagno sis will correspond to a range of values for a predictor. If ...
Toward a Theory of Intelligence - Boston College Computer Science
... how to play chess well only by being told what to do. Being told what to do can help, but lots of playing (which is to say, lots of examples) generally help more. Few children, if any, have ever learned the meaning of the word “dog” from detailed instructions that tell them how to recognize one. Eve ...
... how to play chess well only by being told what to do. Being told what to do can help, but lots of playing (which is to say, lots of examples) generally help more. Few children, if any, have ever learned the meaning of the word “dog” from detailed instructions that tell them how to recognize one. Eve ...
E-connections of Description Logics
... blow-up, we obtain an upper complexity bound for the E-connection that is one nondeterministic exponential higher than the complexity of the component logics. It is currently unknown whether this complexity is optimal in the general case. However, it seems that in many natural cases the increase in ...
... blow-up, we obtain an upper complexity bound for the E-connection that is one nondeterministic exponential higher than the complexity of the component logics. It is currently unknown whether this complexity is optimal in the general case. However, it seems that in many natural cases the increase in ...
Spiking Neural Networks: Principles and Challenges
... networks, for spiking neural networks we can distinguish between unsupervised learning, and supervised learning: Unsupervised Learning Here data is provided without label, and there is no feedback to the network about its performance. The typical task is to detect and react to statistical correlatio ...
... networks, for spiking neural networks we can distinguish between unsupervised learning, and supervised learning: Unsupervised Learning Here data is provided without label, and there is no feedback to the network about its performance. The typical task is to detect and react to statistical correlatio ...
Robust Reinforcement Learning Control with Static and Dynamic
... environment. This is much like the trial-and-error approach from animal learning and psychology. The goal of reinforcement learning is to devise a control algorithm, called a policy, that selects optimal actions for each observed state. By optimal, we mean those actions which produce the highest rei ...
... environment. This is much like the trial-and-error approach from animal learning and psychology. The goal of reinforcement learning is to devise a control algorithm, called a policy, that selects optimal actions for each observed state. By optimal, we mean those actions which produce the highest rei ...
Exploring the Complex Interplay between AI and Consciousness
... educational material has been recalled after 50 years (Bahrick, 1984). No effect sizes nearly as long-lasting as these have been reported in the subliminal learning literature (Elliott & Dolan, 1998). Conscious access greatly facilitates most types of learning. Once again consider perceptual learnin ...
... educational material has been recalled after 50 years (Bahrick, 1984). No effect sizes nearly as long-lasting as these have been reported in the subliminal learning literature (Elliott & Dolan, 1998). Conscious access greatly facilitates most types of learning. Once again consider perceptual learnin ...
Dr. Eick`s Introduction to AI
... • Computers show promise to control the current waste of energy and other natural resources. • Computer can work in environment that are unsuitable for human beings. • If computers control everything --- who controls the computers? • If computers are intelligent what civil rights should be given to ...
... • Computers show promise to control the current waste of energy and other natural resources. • Computer can work in environment that are unsuitable for human beings. • If computers control everything --- who controls the computers? • If computers are intelligent what civil rights should be given to ...
Learning in the oculomotor system: from molecules to behavior
... changes. Some clues are provided by in vitro studies, which have begun to identify forms of synaptic plasticity in the circuit for the VOR. One particular form of plasticity in the cerebellar cortex has received the most attention, long-term depression of synapses from parallel fibers to Purkinje ce ...
... changes. Some clues are provided by in vitro studies, which have begun to identify forms of synaptic plasticity in the circuit for the VOR. One particular form of plasticity in the cerebellar cortex has received the most attention, long-term depression of synapses from parallel fibers to Purkinje ce ...
Autonomously Learning an Action Hierarchy Using a Learned
... (although any action on the corresponding magnitude variable of Y is excluded from AC to prevent infinite regress). (2) The qualitative action qa(X, x) brings about the antecedent event of r. (3) QLAP subtracts those actions whose goal is already achieved in state s. To construct Tr : Sr × Asr → Sr ...
... (although any action on the corresponding magnitude variable of Y is excluded from AC to prevent infinite regress). (2) The qualitative action qa(X, x) brings about the antecedent event of r. (3) QLAP subtracts those actions whose goal is already achieved in state s. To construct Tr : Sr × Asr → Sr ...
Guided Cost Learning: Deep Inverse Optimal Control via Policy
... learning algorithm based on policy optimization with local linear models, building on prior work in reinforcement learning (Levine & Abbeel, 2014). In this approach, as illustrated in Figure 1, the cost function is learned in the inner loop of a policy search procedure, using samples collected for p ...
... learning algorithm based on policy optimization with local linear models, building on prior work in reinforcement learning (Levine & Abbeel, 2014). In this approach, as illustrated in Figure 1, the cost function is learned in the inner loop of a policy search procedure, using samples collected for p ...
Intelligent Tutoring Systems: An Overview
... From the early years of the systematic use of Instructional design, educational scientists wanted to use the results of artificial intelligence to support authors, developers, researchers, in their pedagogical work to create “automatic” course designing machines or make the built in process more and ...
... From the early years of the systematic use of Instructional design, educational scientists wanted to use the results of artificial intelligence to support authors, developers, researchers, in their pedagogical work to create “automatic” course designing machines or make the built in process more and ...
Deep learning with COTS HPC systems
... dataset of 200x200 color images so each image may be thought of as a 3D grid of 200-by-200-by-3 values, and each mini-batch is just an array of M such 3D grids. The output of the network layer can similarly be represented as a 4D grid of M -by-r-by-r-by-d responses, where r and d are determined by t ...
... dataset of 200x200 color images so each image may be thought of as a 3D grid of 200-by-200-by-3 values, and each mini-batch is just an array of M such 3D grids. The output of the network layer can similarly be represented as a 4D grid of M -by-r-by-r-by-d responses, where r and d are determined by t ...
My second proposal is a project based on the “double
... action tower. Keep in mind however, that all of these model assertions are subject to a truthmaintenance system that continuously updates them as the (sensed) environment changes. A user can specify a tower to be built by calling the top-level T-R program, maketower(x), with x instantiated to whatev ...
... action tower. Keep in mind however, that all of these model assertions are subject to a truthmaintenance system that continuously updates them as the (sensed) environment changes. A user can specify a tower to be built by calling the top-level T-R program, maketower(x), with x instantiated to whatev ...
My second proposal is a project based on the “double
... action tower. Keep in mind however, that all of these model assertions are subject to a truthmaintenance system that continuously updates them as the (sensed) environment changes. A user can specify a tower to be built by calling the top-level T-R program, maketower(x), with x instantiated to whatev ...
... action tower. Keep in mind however, that all of these model assertions are subject to a truthmaintenance system that continuously updates them as the (sensed) environment changes. A user can specify a tower to be built by calling the top-level T-R program, maketower(x), with x instantiated to whatev ...
The Instance Store: DL Reasoning with Large Numbers of Individuals
... two concepts would require DL reasoning (which we are trying to avoid), the optimised iS only checks for syntactic equality using a database lookup. (The chances of detecting equivalence via syntactic checks could be increased by transforming concepts into a syntactic normal form, as is done by opti ...
... two concepts would require DL reasoning (which we are trying to avoid), the optimised iS only checks for syntactic equality using a database lookup. (The chances of detecting equivalence via syntactic checks could be increased by transforming concepts into a syntactic normal form, as is done by opti ...
Predicting Classifier Combinations
... tion can be compared to the ground-truth information. Since our meta-learning approach is a classification task, typically classification measures such as classification accuracy might be used to evaluate the performance of the prediction model. However, this would lead to the following issues: If m ...
... tion can be compared to the ground-truth information. Since our meta-learning approach is a classification task, typically classification measures such as classification accuracy might be used to evaluate the performance of the prediction model. However, this would lead to the following issues: If m ...
Reinforcement Learning and Automated Planning
... • The solution to such a problem is a sequence of actions, which if applied to I leads to a state S’ such as S’ ⊇ G. Usually, in the description of domains, action schemas (also called operators) are used instead of actions. Action schemas contain variables that can be instantiated using the availab ...
... • The solution to such a problem is a sequence of actions, which if applied to I leads to a state S’ such as S’ ⊇ G. Usually, in the description of domains, action schemas (also called operators) are used instead of actions. Action schemas contain variables that can be instantiated using the availab ...
The SCHOLAR Legacy: A New Look at the Affordances of Semantic
... extraction of ontologies from text corpora, now encourage a vision in which intelligent tutoring agents have access to forms of knowledge representation that allow them to more fully “understand” something of what they are talking about with learners. These developments have important implications f ...
... extraction of ontologies from text corpora, now encourage a vision in which intelligent tutoring agents have access to forms of knowledge representation that allow them to more fully “understand” something of what they are talking about with learners. These developments have important implications f ...
(Statistical) Relational Learning
... How to deal with millions of interrelated research papers ? How to accumulate general knowledge automatically from the Web ? How to deal with billions of shared users’ perceptions stored at massive scale ? How to realize the vision of social search? Kristian Kersting (Statistical) Relational Learnin ...
... How to deal with millions of interrelated research papers ? How to accumulate general knowledge automatically from the Web ? How to deal with billions of shared users’ perceptions stored at massive scale ? How to realize the vision of social search? Kristian Kersting (Statistical) Relational Learnin ...
Discriminative Improvements to Distributional Sentence Similarity
... Figure 2 presents results for a range of latent dimensionalities. Supervised learning identifies the important dimensions in the latent space, yielding significantly better performance that the similaritybased classification from the previous experiment. In Table 3, we compare against prior publishe ...
... Figure 2 presents results for a range of latent dimensionalities. Supervised learning identifies the important dimensions in the latent space, yielding significantly better performance that the similaritybased classification from the previous experiment. In Table 3, we compare against prior publishe ...
A Neural Network of Adaptively Timed Reinforcement
... timing, reinforcement learning, attention, and motor learning differ, yet are linked in the control of behavior. Thus the exposition needs to describe several different types of circuits that form part of a larger neural system. These results were announced in Grossberg and Merrill (1991 ). Part I, ...
... timing, reinforcement learning, attention, and motor learning differ, yet are linked in the control of behavior. Thus the exposition needs to describe several different types of circuits that form part of a larger neural system. These results were announced in Grossberg and Merrill (1991 ). Part I, ...
9781111533960_PPT_ch13
... • In Baltimore County, an expert system was developed so that detectives could analyze information about burglary sites and identify possible suspects • Detectives could enter statements about burglaries, such as neighborhood characteristics, the type of property stolen, and the type of entry used; ...
... • In Baltimore County, an expert system was developed so that detectives could analyze information about burglary sites and identify possible suspects • Detectives could enter statements about burglaries, such as neighborhood characteristics, the type of property stolen, and the type of entry used; ...
Business Process Modelling Examples
... 1. What were the benefits of creating “As-Is” models of current business processed at WSP? 2. How did information systems help identify problem areas in the feed logistics process? 3. How did information systems help improve the management of feed logistics? 4. Are information systems necessary for ...
... 1. What were the benefits of creating “As-Is” models of current business processed at WSP? 2. How did information systems help identify problem areas in the feed logistics process? 3. How did information systems help improve the management of feed logistics? 4. Are information systems necessary for ...
Reasoning with Axioms: Theory and Practice
... with the (tableaux) satisfiability algorithm (lazy unfolding) leads to a significant improvement in performance [BFH+ 94]. More recently, experiments with the FaCT system have shown that reasoning becomes hopelessly intractable when internalisation is used to deal with larger terminologies [Hor98]. ...
... with the (tableaux) satisfiability algorithm (lazy unfolding) leads to a significant improvement in performance [BFH+ 94]. More recently, experiments with the FaCT system have shown that reasoning becomes hopelessly intractable when internalisation is used to deal with larger terminologies [Hor98]. ...
Unifying Logical and Statistical AI - Washington
... logical KB, becoming equivalent to one in the limit of all infinite weights. When the weights are positive and finite, and all formulas are simultaneously satisfiable, the satisfying solutions are the modes of the distribution represented by the ground Markov network. Most importantly, Markov logic ...
... logical KB, becoming equivalent to one in the limit of all infinite weights. When the weights are positive and finite, and all formulas are simultaneously satisfiable, the satisfying solutions are the modes of the distribution represented by the ground Markov network. Most importantly, Markov logic ...