- ePrints Soton
... correctly and efficiently. Since the software crisis was recognized in the 1960s and 1970s, significant research and development effort has been directed at making it easier and cheaper to engineer increasingly complex software systems. Despite significant progress, software engineering’s fundamenta ...
... correctly and efficiently. Since the software crisis was recognized in the 1960s and 1970s, significant research and development effort has been directed at making it easier and cheaper to engineer increasingly complex software systems. Despite significant progress, software engineering’s fundamenta ...
Fixed-parameter complexity in AI and nonmonotonic reasoning
... 2P -complete [15]. Note, however, that completeness results for parameterized classes are more difficult to obtain. In fact, for obtaining our completeness result we had to resort to the general version of circumscription (called P ;Z-circumscription) where the propositional letters of the theory t ...
... 2P -complete [15]. Note, however, that completeness results for parameterized classes are more difficult to obtain. In fact, for obtaining our completeness result we had to resort to the general version of circumscription (called P ;Z-circumscription) where the propositional letters of the theory t ...
Instinctive Computing
... Yang Cai, Instinctive Computing, in book “Human Computing”, M. Pantic, etc.(eds), LNAI 4451, Springer, 2007 ...
... Yang Cai, Instinctive Computing, in book “Human Computing”, M. Pantic, etc.(eds), LNAI 4451, Springer, 2007 ...
Building a Constraint Solver that Learns. In Proceedings of the AAAI
... game player, learned to play19 different two-dimensional, finite-board games as well or better than the best human experts (Epstein, 2001). Ariadne, a FORR-based pathfinder for two-dimensional mazes, learned to find its way efficiently through complex mazes modeled on real-world spaces (Epstein, 199 ...
... game player, learned to play19 different two-dimensional, finite-board games as well or better than the best human experts (Epstein, 2001). Ariadne, a FORR-based pathfinder for two-dimensional mazes, learned to find its way efficiently through complex mazes modeled on real-world spaces (Epstein, 199 ...
David Bergman Assistant Professor Operations and Information
... • Annual award recognizing best student paper in the area of Operations Research or Algorithms, Combinatorics, and Optimization at Carnegie Mellon University William Larimer Mellon Fellowship ...
... • Annual award recognizing best student paper in the area of Operations Research or Algorithms, Combinatorics, and Optimization at Carnegie Mellon University William Larimer Mellon Fellowship ...
ppt - LaDiSpe - Politecnico di Torino
... To embody (verb) = to manifest or personify in concrete form; to incarnate; to incorporate, to unite into one body Embodiment is the way in which human (or any other animal) psychology arises from the brain & body physiology Embodiment theory was introduced into AI by Rodney Brooks in the ‘80s ...
... To embody (verb) = to manifest or personify in concrete form; to incarnate; to incorporate, to unite into one body Embodiment is the way in which human (or any other animal) psychology arises from the brain & body physiology Embodiment theory was introduced into AI by Rodney Brooks in the ‘80s ...
Powerpoint presentation 3
... and see if the database satisfies the conditionals: `If an animal has fur, it is a mammal’ `If an animal has feathers, it is a bird’ `If an animal is a bird, it can fly’ `If an animal is a bird, it lays eggs’ `If an animal has scales, it is a fish’ `If an animal is a fish, it can swim’ `If an animal ...
... and see if the database satisfies the conditionals: `If an animal has fur, it is a mammal’ `If an animal has feathers, it is a bird’ `If an animal is a bird, it can fly’ `If an animal is a bird, it lays eggs’ `If an animal has scales, it is a fish’ `If an animal is a fish, it can swim’ `If an animal ...
Neural Networks
... for probing into neural networks help provide some explanation – Neural networks are best approached as black boxes with mysterious internal workings Slide 7 ...
... for probing into neural networks help provide some explanation – Neural networks are best approached as black boxes with mysterious internal workings Slide 7 ...
The errors, insights and lessons of famous AI predictions
... these risks are reasonable, and, if so, when and how AI is likely to be developed. Even if the risks turn out to be overblown, simply knowing the reliability of general AI predictions will have great social and economic consequences. The aim of this paper is thus to construct a framework and tools ...
... these risks are reasonable, and, if so, when and how AI is likely to be developed. Even if the risks turn out to be overblown, simply knowing the reliability of general AI predictions will have great social and economic consequences. The aim of this paper is thus to construct a framework and tools ...
Answering Subcognitive Turing Test Questions: A
... screen the examiner from information that is not relevant to determining intelligence, such as the physical appearance of the subjects. The task of the examiner is to guess who is the human subject and who is not, by asking various questions to the two subjects and studying the replies. Both subject ...
... screen the examiner from information that is not relevant to determining intelligence, such as the physical appearance of the subjects. The task of the examiner is to guess who is the human subject and who is not, by asking various questions to the two subjects and studying the replies. Both subject ...
Answering Subcognitive Turing Test Questions: A Reply
... screen the examiner from information that is not relevant to determining intelligence, such as the physical appearance of the subjects. The task of the examiner is to guess who is the human subject and who is not, by asking various questions to the two subjects and studying the replies. Both subject ...
... screen the examiner from information that is not relevant to determining intelligence, such as the physical appearance of the subjects. The task of the examiner is to guess who is the human subject and who is not, by asking various questions to the two subjects and studying the replies. Both subject ...
Management Information Systems 11e
... Figure 11-6: Requirements of knowledge work systems Examples of Knowledge Work Systems Pick up any business or technology magazine or surf news channels and you'll find numerous examples of how companies are using knowledge work systems to re-create their core processes, create new products or serv ...
... Figure 11-6: Requirements of knowledge work systems Examples of Knowledge Work Systems Pick up any business or technology magazine or surf news channels and you'll find numerous examples of how companies are using knowledge work systems to re-create their core processes, create new products or serv ...
What is a plan?
... The main unifying theme is the idea of an intelligent agent. We define AI as the study of agents that receive percepts from the environment and perform actions. Each such agent implements a function that maps percept sequences to actions, and we cover different ways to represent these func- tions, s ...
... The main unifying theme is the idea of an intelligent agent. We define AI as the study of agents that receive percepts from the environment and perform actions. Each such agent implements a function that maps percept sequences to actions, and we cover different ways to represent these func- tions, s ...
CUUS366-02 clean wjc
... In the late 1980s, an artificial intelligence (AI) researcher trying to untangle controversies about the nature of knowledge, memory, and behavior would have been surrounded by perplexed computer science and psychology colleagues who viewed situated cognition ideas as fool’s gold – or even suggested ...
... In the late 1980s, an artificial intelligence (AI) researcher trying to untangle controversies about the nature of knowledge, memory, and behavior would have been surrounded by perplexed computer science and psychology colleagues who viewed situated cognition ideas as fool’s gold – or even suggested ...
A Mixed-Initiative Approach to Rule Refinement for Knowledge
... after having learned the rule from Figure 3, Disciple attempts to “Determine whether Mark White can be a PhD advisor for Tom Evan in Information Security.” Because the PUB condition of the rule from Figure 3 is satisfied for this task, Disciple applies it and proposes the reduction to the expert: “D ...
... after having learned the rule from Figure 3, Disciple attempts to “Determine whether Mark White can be a PhD advisor for Tom Evan in Information Security.” Because the PUB condition of the rule from Figure 3 is satisfied for this task, Disciple applies it and proposes the reduction to the expert: “D ...
Intelligent Decision Support Systems- A Framework
... 5. IDSS : A Framework There are three fundamental components of a DSS (Andrew, 1991). • Database Management Subsystem: It includes a database which contains data that are relevant to the class of problems for which the DSS has been designed and Database Management System (DBMS) which is a software t ...
... 5. IDSS : A Framework There are three fundamental components of a DSS (Andrew, 1991). • Database Management Subsystem: It includes a database which contains data that are relevant to the class of problems for which the DSS has been designed and Database Management System (DBMS) which is a software t ...
Week10-BUAD283-Chp04
... What Expert Systems Can Do Handle massive amounts of information Reduce errors Reduce costs Improve customer service Provide consistency in decision making Maintain an organization’s knowledge asset ...
... What Expert Systems Can Do Handle massive amounts of information Reduce errors Reduce costs Improve customer service Provide consistency in decision making Maintain an organization’s knowledge asset ...
PDF
... 1943 McCulloch and Pitts show networks of neurons can compute and learn any function 1950 Shannon and Turing wrote chess programs 1951 Minsky and Edmonds build the first neural network computer (SNARC) 1956 Dartmouth Conference – Newell and Simon brought a reasoning program “The Logic Theorist” whic ...
... 1943 McCulloch and Pitts show networks of neurons can compute and learn any function 1950 Shannon and Turing wrote chess programs 1951 Minsky and Edmonds build the first neural network computer (SNARC) 1956 Dartmouth Conference – Newell and Simon brought a reasoning program “The Logic Theorist” whic ...
AAAI Proceedings Template - Electronics and Computer Science
... properties, like all other physical properties. In contrast, with the "other-minds" problem, we each know perfectly well what it is that would be missing if others did not feel at all, as we do: feeling. But “living” has no counterpart for this: Other systems are alive because they have the objectiv ...
... properties, like all other physical properties. In contrast, with the "other-minds" problem, we each know perfectly well what it is that would be missing if others did not feel at all, as we do: feeling. But “living” has no counterpart for this: Other systems are alive because they have the objectiv ...
What Is Approximate Reasoning?
... Since by this definition, ⊥ contains no real information, one could argue about additional constraints for the error function with respect to this distinguished element, e.g., e(⊥, y) ≥ supx∈X {e(x, y)} or even e(⊥, y) ≥ supx,z∈X {e(x, z)}. We do not need to impose these in general, however. After h ...
... Since by this definition, ⊥ contains no real information, one could argue about additional constraints for the error function with respect to this distinguished element, e.g., e(⊥, y) ≥ supx∈X {e(x, y)} or even e(⊥, y) ≥ supx,z∈X {e(x, z)}. We do not need to impose these in general, however. After h ...
Introduction to AI - Florida Tech Department of Computer Sciences
... Early Computers = Calculator plus stored program • The Dream: Turing test, 1950 • Look Ma, No Hands! 1952-69 – Samuel’s checkers program: game playing – Newell-Simon’s Logic Theorist: proving math theorems – Geltner’s Geometry Engine: geometry theorems ...
... Early Computers = Calculator plus stored program • The Dream: Turing test, 1950 • Look Ma, No Hands! 1952-69 – Samuel’s checkers program: game playing – Newell-Simon’s Logic Theorist: proving math theorems – Geltner’s Geometry Engine: geometry theorems ...
A NEW REAL TIME LEARNING ALGORITHM 1. Introduction One
... the condition could be satisfied by setting all estimates to 0). In LRTA*, the updating procedures are performed only for the nodes that the agent actually visits. The following characteristic is known [1]: • In a finite number of nodes with positive link costs, in which there exists a path from eve ...
... the condition could be satisfied by setting all estimates to 0). In LRTA*, the updating procedures are performed only for the nodes that the agent actually visits. The following characteristic is known [1]: • In a finite number of nodes with positive link costs, in which there exists a path from eve ...
1. Introduction to Intelligent Systems
... performance in reaching its objectives i.e: having experiences where the system learned which actions best let it reach its objectives. (Likewise: a person is not intelligent in all areas of knowledge, only in areas where they had experiences). System - Part of the universe, with a limited extensi ...
... performance in reaching its objectives i.e: having experiences where the system learned which actions best let it reach its objectives. (Likewise: a person is not intelligent in all areas of knowledge, only in areas where they had experiences). System - Part of the universe, with a limited extensi ...
Angry-HEX: An Artificial Player for Angry Birds Based on Declarative
... participating agent runs on a client which connects the browser game to the server according to a given protocol. An artificial player can also obtain the current reference scores for each level, and can prompt the server for executing a shot, which will in turn be performed in the corresponding gam ...
... participating agent runs on a client which connects the browser game to the server according to a given protocol. An artificial player can also obtain the current reference scores for each level, and can prompt the server for executing a shot, which will in turn be performed in the corresponding gam ...