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Performance Study of Recent Swarm Optimization Techniques
Performance Study of Recent Swarm Optimization Techniques

Pathfinding Algorithms in Multi
Pathfinding Algorithms in Multi

Qualitative Reasoning about Electrical Circuits using Series
Qualitative Reasoning about Electrical Circuits using Series

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Michał Farnik A hat guessing game

New approaches for heuristic search: linkage with artificial
New approaches for heuristic search: linkage with artificial

... A neural network can be organized, by appropriate choice of topology, states and functions, to behave as an optimizing system (at least locally) for a combinatorial problem. The function to be optimized over a specified set is replaced by an energy function to be minimized, typically over a larger ( ...
Belief Updating by Enumerating High-Probability
Belief Updating by Enumerating High-Probability

... signments assign fewer variables in abduc­ tive explanations than do schemes assign­ ing values to all evidentially supported vari­ ables. We use IB assignments to approxi­ mate marginal probabilities in Bayesian be­ lief networks. Recent work in belief up­ dating for Bayes networks attempts to ap­ ...
(G5AIAI) - 2001/02
(G5AIAI) - 2001/02

... The utility functions are shown in the search tree above. The student should initially assign values to the terminal states and then propagate these up the tree, depending on whether it is min or max’s turn to move (min minimises the utility function of its child nodes, max maximises). The student s ...
Boundedly Rational Nash Equilibrium: A
Boundedly Rational Nash Equilibrium: A

artificial intelligence - ABIT Group of Institutions
artificial intelligence - ABIT Group of Institutions

... Remote Agent program became the first on-board autonomous planning program to control the scheduling of operations for a spacecraft (Jonsson et al., 2000). Remote Agent generated plans from high-level goals specified from the ground, and it monitored the operation of the spacecraft as the plans were ...
PDF - University of California, Irvine
PDF - University of California, Irvine

An application of ranking methods: retrieving the importance order of
An application of ranking methods: retrieving the importance order of

... well-tried and tested method, the "reverse approach" has had much less notice as it deserves. This means that transforming between decision factor weights and ranking information is possible in either direction: from weights into ranking (which is the conventional AHP approach), and also from rankin ...
D s (vp i )
D s (vp i )

Distribution of Strategies in a Spatial Multi-Agent Game
Distribution of Strategies in a Spatial Multi-Agent Game

Cumulative distribution networks and the derivative-sum
Cumulative distribution networks and the derivative-sum

... sages. If we denote ∂xk µφc →Xk (xk ) = λφc →Xk (xk ) i h and ∂xk µXk →φc (xk ) = λXk →φc (xk ), we can write DSP using two sets of messages µ and λ, as shown in Figure 6. The joint PDF is then given at the root node Xr by P (x) = λXr →∅ (xr ). We need only to pre-compute the derivatives of the φc ’ ...
Language-based Games - Cornell Computer Science
Language-based Games - Cornell Computer Science

On the Formal Semantics of IF-like Logics
On the Formal Semantics of IF-like Logics

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Approximate Planning in POMDPs with Macro

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Finding the M Most Probable Configurations using Loopy Belief

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BASIC IDEAS OF A GENERAL THEORY OF STATISTICAL

... [1]. These assumptions are made here merely for the purpose of simplifying the discussion. A decision rule 5, that is, a rule for carrying out experimentation and making a final decision d, can be given in terms of a sequence of real-valued and Borei ...
inf orms O R
inf orms O R

... customers have been pre-ordered by decreasing values so that v1  v2  · · ·  vn . The problem is to choose the set of customers A ⊆ C to whom the promotional sale will be made available. If m is large, more clients should be included; while for small m, one should be more selective to avoid high-r ...
Repeated Games with Differential Time Preferences
Repeated Games with Differential Time Preferences

... that the patient player prefers in later stages. The gains from this trade can push the players’ overall utility outside the feasible set of the stage-game. Therefore, the set of all feasible payoffs of the repeated game is typically larger than that of the stage-game. The second fact, that not ever ...
Mean-Field Game Modeling the Bandwagon Effect with Activation
Mean-Field Game Modeling the Bandwagon Effect with Activation

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PSO Algorithm with Self Tuned Parameter for

... regime leads to the fabrication of billions of transistors in a single chip. The number of transistors per die will still grow drastically in near future, which increases complexity and thereby imposes enormous challenges in VLSI for physical layer design, especially in routing. In order to handle t ...
Continuous Time Contests with Private Information
Continuous Time Contests with Private Information

Solution Manual Game Theory: An Introduction
Solution Manual Game Theory: An Introduction

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Minimax

Minimax (sometimes MinMax or MM) is a decision rule used in decision theory, game theory, statistics and philosophy for minimizing the possible loss for a worst case (maximum loss) scenario. Originally formulated for two-player zero-sum game theory, covering both the cases where players take alternate moves and those where they make simultaneous moves, it has also been extended to more complex games and to general decision making in the presence of uncertainty.
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