AI Techniques for Personalized Recommendation Tutorial
... whether on the web, through mobile interfaces, or on traditional desktop interfaces. This tutorial first reviews the types of personalized recommendation that are being used commercially and in research systems. It then looks at the broad range of artificial intelligence techniques that have been de ...
... whether on the web, through mobile interfaces, or on traditional desktop interfaces. This tutorial first reviews the types of personalized recommendation that are being used commercially and in research systems. It then looks at the broad range of artificial intelligence techniques that have been de ...
Multi agent systems simulator in Common Lisp
... science research. Before we can study AI, we must define what AI actually is. There are two main branches of AI, each with two subcategories based on their aims. Some researchers base AI on human intelligence, and believe that true AI should be as close to human intelligence as possible. Other resea ...
... science research. Before we can study AI, we must define what AI actually is. There are two main branches of AI, each with two subcategories based on their aims. Some researchers base AI on human intelligence, and believe that true AI should be as close to human intelligence as possible. Other resea ...
Selforganizology: A more detailed description
... probabilistic optimization-searching method which can automatically obtain and guide optimized search space, and adaptively adjust the search direction without determinant rules. These properties make genetic algorithm widely use in combinatorial optimization, machine learning, signal processing, ad ...
... probabilistic optimization-searching method which can automatically obtain and guide optimized search space, and adaptively adjust the search direction without determinant rules. These properties make genetic algorithm widely use in combinatorial optimization, machine learning, signal processing, ad ...
Computational Models of Emotion and Cognition
... load emotional cognitive operators and memory mechanisms for the modeling of a very specific set of emotional effects. On the other hand, other systems have sophisticated emotional theoretical bases, but are built using BDI or other simple models of cognition. We believe that a system with a broad, ...
... load emotional cognitive operators and memory mechanisms for the modeling of a very specific set of emotional effects. On the other hand, other systems have sophisticated emotional theoretical bases, but are built using BDI or other simple models of cognition. We believe that a system with a broad, ...
CTL AgentSpeak(L): a specification language for agent programs
... Our main contribution is the definition of the semantics of the CT L temporal operators in terms of a Kripke structure, produced by a transition system defining the operational semantics of AgentSpeak(L). The semantics of the intentional operators is adopted from the work of Bordini et al. [1]. As a ...
... Our main contribution is the definition of the semantics of the CT L temporal operators in terms of a Kripke structure, produced by a transition system defining the operational semantics of AgentSpeak(L). The semantics of the intentional operators is adopted from the work of Bordini et al. [1]. As a ...
CS 561a: Introduction to Artificial Intelligence
... • Advantages: 1) More general 2) Its goal of rationality is well defined CS 561, Lecture 1 ...
... • Advantages: 1) More general 2) Its goal of rationality is well defined CS 561, Lecture 1 ...
Intelligent Agents. - Home ANU
... There are several basic agent architectures: reflex, reflex with state, goal-based, utility-based Learning can be added to any basic architecture and is indeed essential for satisfactory performance in many applications. Rationality requires a learning component – it is necessary to know as much abo ...
... There are several basic agent architectures: reflex, reflex with state, goal-based, utility-based Learning can be added to any basic architecture and is indeed essential for satisfactory performance in many applications. Rationality requires a learning component – it is necessary to know as much abo ...
Multiagent Systems: A Survey from a Machine Learning Perspective
... naturally approached from an omniscient perspective—because a global view is given—or with centralized control—because no parallel actions are possible and there is no action uncertainty [Decker, 1996b]. Single-agent systems should be used in such cases. Multiagent systems can also be useful for the ...
... naturally approached from an omniscient perspective—because a global view is given—or with centralized control—because no parallel actions are possible and there is no action uncertainty [Decker, 1996b]. Single-agent systems should be used in such cases. Multiagent systems can also be useful for the ...
imperfect information in electronic negotiations: an empirical study
... The electronic automating of negotiations was forecasted by [Davis and Smith 1983] more than 20 years ago. However, the automation level of current negotiation systems is still different (fully automated, process support and hybrid negotiation models [Rebstock 2001]). Fully automated models work wit ...
... The electronic automating of negotiations was forecasted by [Davis and Smith 1983] more than 20 years ago. However, the automation level of current negotiation systems is still different (fully automated, process support and hybrid negotiation models [Rebstock 2001]). Fully automated models work wit ...
Analyzing Myopic Approaches for Multi
... solution found is still a decentralized solution. We chose this approach for two reasons. First, individual agents often lack the computational resources necessary to generate high quality solutions. Second, individual agents often lack a global view of the problem, which while not strictly necessar ...
... solution found is still a decentralized solution. We chose this approach for two reasons. First, individual agents often lack the computational resources necessary to generate high quality solutions. Second, individual agents often lack a global view of the problem, which while not strictly necessar ...
Agent Composition Synthesis based on ATL
... generator” [18] i.e., an implicit representation of all possible controllers realizing a composition. The results of this paper are of interest for at least two contrasting reasons. First, from the point of view of agent composition, it gives access to some of the most modern ...
... generator” [18] i.e., an implicit representation of all possible controllers realizing a composition. The results of this paper are of interest for at least two contrasting reasons. First, from the point of view of agent composition, it gives access to some of the most modern ...
Multi-objective Optimization Using Particle Swarm Optimization
... • A swarm consists of N particles in a Ddimensional search space. Each particle holds a position (which is a candidate solution to the problem) and a velocity (which means the flying direction and step of the particle). • Each particle successively adjust its position toward the global optimum based ...
... • A swarm consists of N particles in a Ddimensional search space. Each particle holds a position (which is a candidate solution to the problem) and a velocity (which means the flying direction and step of the particle). • Each particle successively adjust its position toward the global optimum based ...
Comprehensive Introduction to Intelligent Software Agents for
... What is the relative cost of achieving goals A, B, and C above? What is the relative probability of even being able to achieve goals A, B, and C without significant, expensive research and development? The point is that setting the right expectations helps one understand what is actually practical a ...
... What is the relative cost of achieving goals A, B, and C above? What is the relative probability of even being able to achieve goals A, B, and C without significant, expensive research and development? The point is that setting the right expectations helps one understand what is actually practical a ...
A distributed problem-solving approach to rule induction
... systems. It can be in the form of data exchange, knowledge transfer, or heuristics migration, where the learning mechanisms involved are relatively simple. It can also be done by extending machine learning techniques developed for single-agent systems, such as explanation-based learning, case-based ...
... systems. It can be in the form of data exchange, knowledge transfer, or heuristics migration, where the learning mechanisms involved are relatively simple. It can also be done by extending machine learning techniques developed for single-agent systems, such as explanation-based learning, case-based ...
Agent based approach to Mass-Oriented Production Planning: Case
... planning techniques. Classical artificial intelligence (AI) and operation research (OR) techniques are currently widely used in nowadays production planning systems. Besides classical linear programming (and related) approaches that have been widely used in the manufacturing problems where the probl ...
... planning techniques. Classical artificial intelligence (AI) and operation research (OR) techniques are currently widely used in nowadays production planning systems. Besides classical linear programming (and related) approaches that have been widely used in the manufacturing problems where the probl ...
Reports on the Twenty-First National Conference on Artificial
... real-world environments. Social scientists who are interested in building models of real-world social environments have traditionally limited themselves to verbal or static game-theoretic equilibrium models, which force them to make unrealistic assumptions such as homogeneity among agents and limit ...
... real-world environments. Social scientists who are interested in building models of real-world social environments have traditionally limited themselves to verbal or static game-theoretic equilibrium models, which force them to make unrealistic assumptions such as homogeneity among agents and limit ...
Reports on the Twenty-First National Conference on Artificial
... real-world environments. Social scientists who are interested in building models of real-world social environments have traditionally limited themselves to verbal or static game-theoretic equilibrium models, which force them to make unrealistic assumptions such as homogeneity among agents and limit ...
... real-world environments. Social scientists who are interested in building models of real-world social environments have traditionally limited themselves to verbal or static game-theoretic equilibrium models, which force them to make unrealistic assumptions such as homogeneity among agents and limit ...
In AI application in a real
... o Reasoning (problem solving), including the pattern (or condition) matching problems o Learning and adaptation (supervised and/or unsupervised) o Search (including data mining) By combining the basic techniques more complex problems can be solved – e.g. computer vision The above-listed techniques a ...
... o Reasoning (problem solving), including the pattern (or condition) matching problems o Learning and adaptation (supervised and/or unsupervised) o Search (including data mining) By combining the basic techniques more complex problems can be solved – e.g. computer vision The above-listed techniques a ...
Distributed Constraint Satisfaction Algorithm for Complex Local
... formalized as a distributed CSP, in which each agent has one local variable, whose domain is a set of obtained local solutions. Then, agents can apply algorithms for the case of a single local variable. The drawback of this method is that when a local problem becomes large and complex, finding all ...
... formalized as a distributed CSP, in which each agent has one local variable, whose domain is a set of obtained local solutions. Then, agents can apply algorithms for the case of a single local variable. The drawback of this method is that when a local problem becomes large and complex, finding all ...
Models and Algorithms for Production Planning
... optimality with the CPLEX MIP solver. More recently, Camargo at al. [4] have considered the similar problem. The authors have proposed the heuristic that solves the problem in a hierarchical way. A genetic algorithm is used to explore a larger set of alloy sequences and a knapsack problem algorithm ...
... optimality with the CPLEX MIP solver. More recently, Camargo at al. [4] have considered the similar problem. The authors have proposed the heuristic that solves the problem in a hierarchical way. A genetic algorithm is used to explore a larger set of alloy sequences and a knapsack problem algorithm ...
Artificial Intelligence: a Promised Land for Web Services
... them well suited for handling cross-organisational decision making. For example, agents can be used to (re)negotiate contracts which would then require: determination of which processes are needed to fulfil the contract; creation of new business processes; and adaptation of existing business process ...
... them well suited for handling cross-organisational decision making. For example, agents can be used to (re)negotiate contracts which would then require: determination of which processes are needed to fulfil the contract; creation of new business processes; and adaptation of existing business process ...
Alan Turing and the Matrix: Intelligent Systems for Law Enforcement
... The notion of crime is somewhat difficult in MMORPGs and virtual worlds. First of all, defining certain types of behavior in virtual worlds as deviant implies almost by definition regulation of the virtual environment by a central authority. For many players however, the different social structures ...
... The notion of crime is somewhat difficult in MMORPGs and virtual worlds. First of all, defining certain types of behavior in virtual worlds as deviant implies almost by definition regulation of the virtual environment by a central authority. For many players however, the different social structures ...