KNOWLEDGE ACQUISITION FOR CLASSIFICATION EXPERT
... Figure 2: The inference structure of Mycin The classification problem solving model describes how a particular problem solver solves a problem. It is not a description of a kind of problem. For example, medical diagnosis cannot always be accomplished by classification. Rather, whenever a problem sol ...
... Figure 2: The inference structure of Mycin The classification problem solving model describes how a particular problem solver solves a problem. It is not a description of a kind of problem. For example, medical diagnosis cannot always be accomplished by classification. Rather, whenever a problem sol ...
Details - John Franco
... Abstract— For solving problems of robot navigation over unknown and changing terrain, many algorithms have been invented. For example, D* Lite, which is a dynamic, incremental search algorithm, is the most successful one. The improved performance of the D* Lite algorithm over other replanning algori ...
... Abstract— For solving problems of robot navigation over unknown and changing terrain, many algorithms have been invented. For example, D* Lite, which is a dynamic, incremental search algorithm, is the most successful one. The improved performance of the D* Lite algorithm over other replanning algori ...
Combining satisfiability techniques from AI and OR
... to both communities, but until recently, the two fields have seldom collaborated. The fields have evolved independently, use different techniques, and each has a unique framework for approaching problems. It is only recently that there have been attempts to build algorithms integrating techniques fr ...
... to both communities, but until recently, the two fields have seldom collaborated. The fields have evolved independently, use different techniques, and each has a unique framework for approaching problems. It is only recently that there have been attempts to build algorithms integrating techniques fr ...
Sample Chapter
... of standard chess playing. Out of all legal moves, only those moves, which bring the board position to a winning position of respective player are captured and stored in procedural part. However, in chess the total ‘legal moves’ are of the order of 10120. Such a large number of moves are difficult t ...
... of standard chess playing. Out of all legal moves, only those moves, which bring the board position to a winning position of respective player are captured and stored in procedural part. However, in chess the total ‘legal moves’ are of the order of 10120. Such a large number of moves are difficult t ...
Artificial Intelligence
... each assignment, including the contribution of each member. All submitted assignments will have to be accompanied by a short documentation as well. There can be at most 3 members in a group. ...
... each assignment, including the contribution of each member. All submitted assignments will have to be accompanied by a short documentation as well. There can be at most 3 members in a group. ...
12.2 Definition of Planning
... New unsatisfied preconditions will be generated for each newly added action. Then you try to satisfy those by using appropriate actions in the same way as was done for goal state initially. You keep on doing that until there is no unsatisfied precondition. ...
... New unsatisfied preconditions will be generated for each newly added action. Then you try to satisfy those by using appropriate actions in the same way as was done for goal state initially. You keep on doing that until there is no unsatisfied precondition. ...
Hardness-Aware Restart Policies
... Gomes et al. [7] demonstrated the effectiveness of randomized restarts on a variety of problems in scheduling, theorem-proving, and planning. In this approach, randomness is added to the branching heuristic of a systematic search algorithm; if the search algorithm does not find a solution within a g ...
... Gomes et al. [7] demonstrated the effectiveness of randomized restarts on a variety of problems in scheduling, theorem-proving, and planning. In this approach, randomness is added to the branching heuristic of a systematic search algorithm; if the search algorithm does not find a solution within a g ...
Document
... planning. • The main problem autonomous robots are interacting with the human-world, because exists many obstacles unexpected events and dinamic environments. ...
... planning. • The main problem autonomous robots are interacting with the human-world, because exists many obstacles unexpected events and dinamic environments. ...
Real-time decision problems: An operational research perspective
... the real-time operation of a courier service company. This illustrative application will be used as a 'running' example throughout the paper. Let us consider a courier operator that receives calls for pick-up and delivery of priority mail. Each request consists of a location and a preferred or due d ...
... the real-time operation of a courier service company. This illustrative application will be used as a 'running' example throughout the paper. Let us consider a courier operator that receives calls for pick-up and delivery of priority mail. Each request consists of a location and a preferred or due d ...
CUSTOMER_CODE SMUDE DIVISION_CODE SMUDE
... knowledge is widely available it is unlikely that it will be worth developing an expert system The problem may be solved using symbolic reasoning techniqures. It should’nt require manual dexterity or physical skill. The problem is well structured and does not require common sense knowledge. Common s ...
... knowledge is widely available it is unlikely that it will be worth developing an expert system The problem may be solved using symbolic reasoning techniqures. It should’nt require manual dexterity or physical skill. The problem is well structured and does not require common sense knowledge. Common s ...
CUSTOMER_CODE SMUDE DIVISION_CODE SMUDE
... knowledge is widely available it is unlikely that it will be worth developing an expert system The problem may be solved using symbolic reasoning techniqures. It should’nt require manual dexterity or physical skill. The problem is well structured and does not require common sense knowledge. Common s ...
... knowledge is widely available it is unlikely that it will be worth developing an expert system The problem may be solved using symbolic reasoning techniqures. It should’nt require manual dexterity or physical skill. The problem is well structured and does not require common sense knowledge. Common s ...
Partially observable Markov decision processes for
... Figure 2. The POMDP model. Arrows indicate probabilistic influence. The parameter S is a set containing the discrete states in which the environment can exist. In the TIS, the state of the environment is a representation of the key in which the musician is playing. There are 25 states, one for each ...
... Figure 2. The POMDP model. Arrows indicate probabilistic influence. The parameter S is a set containing the discrete states in which the environment can exist. In the TIS, the state of the environment is a representation of the key in which the musician is playing. There are 25 states, one for each ...
Chapter 11 - 서울대 : Biointelligence lab
... Heuristic Repair Starts with a proposed solution, which most probably does not satisfy the constraints The operators change a data structure so that it violates fewer constraints ...
... Heuristic Repair Starts with a proposed solution, which most probably does not satisfy the constraints The operators change a data structure so that it violates fewer constraints ...
Research Paper
... capabilities. The game shall take the form of a 2D or 3D-Isometric environment that shall use a grid to implement the question of measurement for movement, weapons range, line of sight, etc. The grid shall be tile-based instead of hex-based, which will make determining the aforementioned factors all ...
... capabilities. The game shall take the form of a 2D or 3D-Isometric environment that shall use a grid to implement the question of measurement for movement, weapons range, line of sight, etc. The grid shall be tile-based instead of hex-based, which will make determining the aforementioned factors all ...
Constraint Modelling: A Challenge for First Order Automated Reasoning (invited talk)
... Our experiments are very much work in progress, so we are in a position only to report preliminary findings rather than the final word. Here are comments on just two toy examples, more to give a flavour than to present systematic results. Proving symmetry We consider the N Queens problem, a staple o ...
... Our experiments are very much work in progress, so we are in a position only to report preliminary findings rather than the final word. Here are comments on just two toy examples, more to give a flavour than to present systematic results. Proving symmetry We consider the N Queens problem, a staple o ...
A Challenge for AI
... the world following the action. Uncertain effects on continuous variables are characterized by probability distributions. Decision-theoretic planning is already known to be quite hard both in theory [20] and in practice. However, there are some characteristics of this domain, which, when taken toget ...
... the world following the action. Uncertain effects on continuous variables are characterized by probability distributions. Decision-theoretic planning is already known to be quite hard both in theory [20] and in practice. However, there are some characteristics of this domain, which, when taken toget ...
2 Components of Information Technology
... 701, 759, 762, 836]. The first intellectual stage involves the following: analysis of a problem and its identification, information search, including revealing the main resource constraints, etc. The second design stage includes a multicriteria description of the problem (generation of alternatives, ...
... 701, 759, 762, 836]. The first intellectual stage involves the following: analysis of a problem and its identification, information search, including revealing the main resource constraints, etc. The second design stage includes a multicriteria description of the problem (generation of alternatives, ...
for taking notes
... optimality of solutions of Breadth-first search The algorithm performs successive depth-first searches with limited depth that is increased each iteration This strategy gives a behaviour similar to breadth-first search but without its spatial complexity because each exploration is depth-first, altho ...
... optimality of solutions of Breadth-first search The algorithm performs successive depth-first searches with limited depth that is increased each iteration This strategy gives a behaviour similar to breadth-first search but without its spatial complexity because each exploration is depth-first, altho ...
w - Amazon S3
... Still looking for a policy (s) New twist: don’t know P or R I.e. we don’t know which states are good or what the actions do Must actually try actions and explore new states -- to boldly go where no Pacman agent has been before ...
... Still looking for a policy (s) New twist: don’t know P or R I.e. we don’t know which states are good or what the actions do Must actually try actions and explore new states -- to boldly go where no Pacman agent has been before ...
Decision-Theoretic Planning for Multi
... 1. Guess a joint policy and write it down in exponential time. This is possible, because a joint policy consists of n mappings from observation histories to actions. Since h ≤ |S|, the number of possible histories is exponentially bounded by the problem description. 2. The DEC-POMDP together with th ...
... 1. Guess a joint policy and write it down in exponential time. This is possible, because a joint policy consists of n mappings from observation histories to actions. Since h ≤ |S|, the number of possible histories is exponentially bounded by the problem description. 2. The DEC-POMDP together with th ...
I I I I I I I I I I I I I I I I I I I
... unique, point-valued probability estimate of some node of interest, plus a standard error of that estimate [Henrion86]. As more computation time is expended, the standard error of the probability decreases. When the algorithm is applied to an influence-diagram problem using Equation 4, it calculates ...
... unique, point-valued probability estimate of some node of interest, plus a standard error of that estimate [Henrion86]. As more computation time is expended, the standard error of the probability decreases. When the algorithm is applied to an influence-diagram problem using Equation 4, it calculates ...
cpsc_20371_20biblio
... The paper “Ant Algorithms for Discrete Optimization” looks at some recent work on ant algorithms for discrete algorithms. The first part of the paper describes the basic biological findings on real ants. Then it describes the concept of ant colony optimization (ACO) meta-heuristics in how a colony o ...
... The paper “Ant Algorithms for Discrete Optimization” looks at some recent work on ant algorithms for discrete algorithms. The first part of the paper describes the basic biological findings on real ants. Then it describes the concept of ant colony optimization (ACO) meta-heuristics in how a colony o ...
IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676,p-ISSN: 2320-3331,
... include the SSSC [5] and the unified power flow controller (UPFC) [6]. The SSSC provides a compensating voltage over both a capacitive and inductive range irrespective of the line current. The magnitude and phase of this inserted ac compensating voltage can be rapidly adjusted by SSSC controls. Seve ...
... include the SSSC [5] and the unified power flow controller (UPFC) [6]. The SSSC provides a compensating voltage over both a capacitive and inductive range irrespective of the line current. The magnitude and phase of this inserted ac compensating voltage can be rapidly adjusted by SSSC controls. Seve ...
Expected Number of Random Duplications Within or Between Lists
... set A of n people (e.g. the students in a class) what is the probability that at least two people have the same birthday. What is sometimes referred to as the “birthday paradox” is the fact that the smallest number n for which this probability is greater than one half is n = 23, an evidently, if not ...
... set A of n people (e.g. the students in a class) what is the probability that at least two people have the same birthday. What is sometimes referred to as the “birthday paradox” is the fact that the smallest number n for which this probability is greater than one half is n = 23, an evidently, if not ...
Document
... • First, the planning process uses constraintsatisfaction techniques and creates lists of recommended and contraindicated substructures. Then the generate-and-test procedure uses the lists generated and required to explore only a limited set of structures. Constrained in this way, generate-and-test ...
... • First, the planning process uses constraintsatisfaction techniques and creates lists of recommended and contraindicated substructures. Then the generate-and-test procedure uses the lists generated and required to explore only a limited set of structures. Constrained in this way, generate-and-test ...
Multi-armed bandit
In probability theory, the multi-armed bandit problem (sometimes called the K- or N-armed bandit problem) is a problem in which a gambler at a row of slot machines (sometimes known as ""one-armed bandits"") has to decide which machines to play, how many times to play each machine and in which order to play them. When played, each machine provides a random reward from a distribution specific to that machine. The objective of the gambler is to maximize the sum of rewards earned through a sequence of lever pulls.Robbins in 1952, realizing the importance of the problem, constructed convergent population selection strategies in ""some aspects of the sequential design of experiments"".A theorem, the Gittins index published first by John C. Gittins gives an optimal policy in the Markov setting for maximizing the expected discounted reward.In practice, multi-armed bandits have been used to model the problem of managing research projects in a large organization, like a science foundation or a pharmaceutical company. Given a fixed budget, the problem is to allocate resources among the competing projects, whose properties are only partially known at the time of allocation, but which may become better understood as time passes.In early versions of the multi-armed bandit problem, the gambler has no initial knowledge about the machines. The crucial tradeoff the gambler faces at each trial is between ""exploitation"" of the machine that has the highest expected payoff and ""exploration"" to get more information about the expected payoffs of the other machines. The trade-off between exploration and exploitation is also faced in reinforcement learning.