Profiles in Innovation: Artificial Intelligence
... Artificial Intelligence (AI) is the apex technology of the information age. The leap from computing built on the foundation of humans telling computers how to act, to computing built on the foundation of computers learning how to act has significant implications for every industry. While this moment ...
... Artificial Intelligence (AI) is the apex technology of the information age. The leap from computing built on the foundation of humans telling computers how to act, to computing built on the foundation of computers learning how to act has significant implications for every industry. While this moment ...
Artificial Cognitive Systems
... A computational engine for interpreting or executing productions ...
... A computational engine for interpreting or executing productions ...
An Introduction to Artificial Intelligence and Legal Reasoning: Using
... curiosity? To what extent and in what ways can artificial intelligence help real lawyers with real legal problems? [4] Computer programs can indeed solve legal problems. The fact that computer programs can model law is not necessarily simply of academic interest. Automated case research is one poten ...
... curiosity? To what extent and in what ways can artificial intelligence help real lawyers with real legal problems? [4] Computer programs can indeed solve legal problems. The fact that computer programs can model law is not necessarily simply of academic interest. Automated case research is one poten ...
The Instance Store: DL Reasoning with Large Numbers of Individuals
... concepts in an ontology) seem able to cope with real world ontologies [18, 14], it is not clear if existing techniques for ABox reasoning (i.e., reasoning about the individuals in an ontology) will be able to cope with realistic sets of instance data. This difficulty arises not so much from the comp ...
... concepts in an ontology) seem able to cope with real world ontologies [18, 14], it is not clear if existing techniques for ABox reasoning (i.e., reasoning about the individuals in an ontology) will be able to cope with realistic sets of instance data. This difficulty arises not so much from the comp ...
Risks and Mitigation Strategies for Oracle AI
... can be copied as much as required. Similarly, if AIs are subject to human-like vicissitudes, such as fatigue or drop in motivation, this can be overcome by taking the entity at the peak of its energy or motivation, and reloading this every time the AI starts to weaken. One could use this, for instan ...
... can be copied as much as required. Similarly, if AIs are subject to human-like vicissitudes, such as fatigue or drop in motivation, this can be overcome by taking the entity at the peak of its energy or motivation, and reloading this every time the AI starts to weaken. One could use this, for instan ...
1 Hybrid Evolutionary Algorithms: Methodologies, Architectures, and
... Summary. Evolutionary computation has become an important problem solving methodology among many researchers. The population-based collective learning process, selfadaptation, and robustness are some of the key features of evolutionary algorithms when compared to other global optimization techniques ...
... Summary. Evolutionary computation has become an important problem solving methodology among many researchers. The population-based collective learning process, selfadaptation, and robustness are some of the key features of evolutionary algorithms when compared to other global optimization techniques ...
Transfer Learning using Computational Intelligence
... techniques (including related methods and approaches) and Type 2 — articles on transfer learning using computational intelligence techniques. Type 3 — articles on related computational intelligence techniques. The search and selection of these articles were performed according to the following five ...
... techniques (including related methods and approaches) and Type 2 — articles on transfer learning using computational intelligence techniques. Type 3 — articles on related computational intelligence techniques. The search and selection of these articles were performed according to the following five ...
AutoTutor - Google Sites
... One grand challenge for education is to scale up the benefits of expert human tutoring for millions of students individually (Bloom, 1984). Computer-assisted learning has long been considered as a solution to this challenge, where an automated tutor simulates the pedagogies and conversational patter ...
... One grand challenge for education is to scale up the benefits of expert human tutoring for millions of students individually (Bloom, 1984). Computer-assisted learning has long been considered as a solution to this challenge, where an automated tutor simulates the pedagogies and conversational patter ...
Rule Insertion and Rule Extraction from Evolving Fuzzy
... The traditional expert systems, based on a fixed set of rules, have significantly contributed to the development of AI and intelligent engineering systems in the past two years. Despite their success, more flexible tools for dynamic rule adaptation, rule extraction from data, and rule insertion in a ...
... The traditional expert systems, based on a fixed set of rules, have significantly contributed to the development of AI and intelligent engineering systems in the past two years. Despite their success, more flexible tools for dynamic rule adaptation, rule extraction from data, and rule insertion in a ...
Selection of Proper Neural Network Sizes and
... training error, but the trained networks lose their generalization ability and cannot process new patterns well (Fig. 11). On the other hand, second-order algorithms, such as the NBN algorithm, work not only significantly faster, but can find good solutions with close to optimal networks (Fig. 9). A ...
... training error, but the trained networks lose their generalization ability and cannot process new patterns well (Fig. 11). On the other hand, second-order algorithms, such as the NBN algorithm, work not only significantly faster, but can find good solutions with close to optimal networks (Fig. 9). A ...
pdf
... 4.1 Default logic for model-based refinement of partial information The causal theory CT of the agent consists of a number of statements a → b for each causal relation from a to b, with a and b atoms. Sometimes included in this set are some facts to indicate that some atoms exclude each other (for e ...
... 4.1 Default logic for model-based refinement of partial information The causal theory CT of the agent consists of a number of statements a → b for each causal relation from a to b, with a and b atoms. Sometimes included in this set are some facts to indicate that some atoms exclude each other (for e ...
Dr. NGUYEN Hoang Phuong Universitat Wien Institut fur
... which is based on the theories of modern bio-medical sciences. The Oriental Medicine has its own unique theory system (Yin-Yang, five elements, the meridians and collaterals system...) which is established on empirical basis of clinical practice. There are many classic works of Oriental Medicine, bu ...
... which is based on the theories of modern bio-medical sciences. The Oriental Medicine has its own unique theory system (Yin-Yang, five elements, the meridians and collaterals system...) which is established on empirical basis of clinical practice. There are many classic works of Oriental Medicine, bu ...
Task Coordination for Non-cooperative Planning Agents
... A task network is thus completed if all ’root’ tasks have been completed; in Figure 1, the task network has been completed if both t1 and t2 have been completed and these tasks can be completed by e.g. performing the tasks t111 , t12 , t21 , t221 , t222 and t23 . Note that the model presented here d ...
... A task network is thus completed if all ’root’ tasks have been completed; in Figure 1, the task network has been completed if both t1 and t2 have been completed and these tasks can be completed by e.g. performing the tasks t111 , t12 , t21 , t221 , t222 and t23 . Note that the model presented here d ...
artificial intelligence - MET Engineering College
... McCarthy convinced Minsky, Claude Shannon, and Nathaniel Rochester to help him bring together U.S. researchers interested in automata theory, neural nets, and the study of intelligence. They organized a two-month workshop at Dartmouth in the summer of 1956. Perhaps the longest-lasting thing to come ...
... McCarthy convinced Minsky, Claude Shannon, and Nathaniel Rochester to help him bring together U.S. researchers interested in automata theory, neural nets, and the study of intelligence. They organized a two-month workshop at Dartmouth in the summer of 1956. Perhaps the longest-lasting thing to come ...
INTELLIGENT REASONING ON NATURAL
... are initially so flexible that they can represent and combine different data modalities (shapes, colors, sounds, meanings) within the same ontology when they are infants. Though human knowledge representations may be specialized as we grow up, our analogy making and even creativity skills seem relat ...
... are initially so flexible that they can represent and combine different data modalities (shapes, colors, sounds, meanings) within the same ontology when they are infants. Though human knowledge representations may be specialized as we grow up, our analogy making and even creativity skills seem relat ...
PDF
... programming formulation) is at least the bound implied by the LP relaxation of the packing formulation; that is, the packing formulation provides a tighter upper bound. However, note that the size of this formulation is exponential in n. In spite of this difficulty, one may apply column generation tec ...
... programming formulation) is at least the bound implied by the LP relaxation of the packing formulation; that is, the packing formulation provides a tighter upper bound. However, note that the size of this formulation is exponential in n. In spite of this difficulty, one may apply column generation tec ...
Towards common-sense reasoning via conditional
... As with Turing’s investigations in AI, the approach we describe has been motivated by reflections on the details of human cognition, as well as on the nature of computation. In particular, much of the AI framework that we describe has been inspired by research in cognitive science attempting to mode ...
... As with Turing’s investigations in AI, the approach we describe has been motivated by reflections on the details of human cognition, as well as on the nature of computation. In particular, much of the AI framework that we describe has been inspired by research in cognitive science attempting to mode ...
Cyberfeminism and Artificial Life
... conflict – with a task which was not clearly right or wrong, black or white, binary. HAL did not understand the purpose of little white lies or what might now be termed complexity. His failure, for Grand, was the failure of the Turing Test as a measure of intelligence. The basis of the Turing Test i ...
... conflict – with a task which was not clearly right or wrong, black or white, binary. HAL did not understand the purpose of little white lies or what might now be termed complexity. His failure, for Grand, was the failure of the Turing Test as a measure of intelligence. The basis of the Turing Test i ...
Adding Local Exploration to Greedy Best-First Search in
... GBFS-LS and GBFS-LRW with hFF for first reaching a given hmin in 2004-notankage #21. in search time, with the largest (763 seconds) for the step from hmin = 2 to hmin = 1, correspond to times when the search is stalled in multiple UHRs. Since the large majority of overall search time is used to inef ...
... GBFS-LS and GBFS-LRW with hFF for first reaching a given hmin in 2004-notankage #21. in search time, with the largest (763 seconds) for the step from hmin = 2 to hmin = 1, correspond to times when the search is stalled in multiple UHRs. Since the large majority of overall search time is used to inef ...
... A process that may solve a given problem, but offers no guarantees of doing so, is called a heuristic for that problem. [Feigenbaum and Feldman 1963. p. I141 O n e gathers from this that they believe there are only two ways to solve a problem: one by thoughtlessly following a sure-fire algorithm; th ...
A Review of Machine Learning for Automated Plan- ning
... traditionally easy-to-code planning domains– like Blocksworld– it is hard to specify the actions’ potential outcomes when the environment is non-deterministic. In extreme cases, like planning for the autonomous control of a Mars Rover (Bresina et al., 2005) or an underwater vehicle (McGann et al., 2 ...
... traditionally easy-to-code planning domains– like Blocksworld– it is hard to specify the actions’ potential outcomes when the environment is non-deterministic. In extreme cases, like planning for the autonomous control of a Mars Rover (Bresina et al., 2005) or an underwater vehicle (McGann et al., 2 ...