Intelligent Agent
... the intelligence seems to belong to the clock’s designer rather than to the clock itself. An agent’s behavior can be based on both its own experience and the built-in knowledge used in constructing the agent for the particular environment in which it operates. A system is autonomous 4 to the extent ...
... the intelligence seems to belong to the clock’s designer rather than to the clock itself. An agent’s behavior can be based on both its own experience and the built-in knowledge used in constructing the agent for the particular environment in which it operates. A system is autonomous 4 to the extent ...
Na¨ıve Inference viewed as Computation
... complex probabilistic information (e.g., Pearl, 1988). Somewhat obstructing it is the knowledge that Bayesian inference is computationally intractable (Cooper, 1990). For some, this intractability does not vitiate the explanatory value of Bayesian inference viewed as an optimal solution for a cognit ...
... complex probabilistic information (e.g., Pearl, 1988). Somewhat obstructing it is the knowledge that Bayesian inference is computationally intractable (Cooper, 1990). For some, this intractability does not vitiate the explanatory value of Bayesian inference viewed as an optimal solution for a cognit ...
Diagrammatic Representation and Reasoning: Some Distinctions
... state. The problems for which such simulation is appropriate are generally prediction problems: given a spatial situation and some proposed actions on, or interaction between, the elements in it, what will be the spatial representation corresponding to the new situation? The simulation is supposed t ...
... state. The problems for which such simulation is appropriate are generally prediction problems: given a spatial situation and some proposed actions on, or interaction between, the elements in it, what will be the spatial representation corresponding to the new situation? The simulation is supposed t ...
Decentralized POMDPs
... a reward depending on the state and the actions of both agents. Finally, each agent receives an individual observation of the new state. This framework allows modeling important real-world tasks for which the models in the previous chapters do not suffice. An example of such a task is load balancing ...
... a reward depending on the state and the actions of both agents. Finally, each agent receives an individual observation of the new state. This framework allows modeling important real-world tasks for which the models in the previous chapters do not suffice. An example of such a task is load balancing ...
Measurements of collective machine intelligence
... has been made. The Turing Test expresses how far a computer is able to resemble a human. It is named after its famous inventor who was very concerned with machine intelligence already in 1950. Turing [57] asked for instance whether computers would one day be able to “think”. He was convinced that on ...
... has been made. The Turing Test expresses how far a computer is able to resemble a human. It is named after its famous inventor who was very concerned with machine intelligence already in 1950. Turing [57] asked for instance whether computers would one day be able to “think”. He was convinced that on ...
A comprehensive survey of multi
... good agent behavior difficult or even impossible. Moreover, in an environment that changes over time, a hardwired behavior may become unappropriate. A reinforcement learning (RL) agent learns by trial-anderror interaction with its dynamic environment [6]–[8]. At each time step, the agent perceives t ...
... good agent behavior difficult or even impossible. Moreover, in an environment that changes over time, a hardwired behavior may become unappropriate. A reinforcement learning (RL) agent learns by trial-anderror interaction with its dynamic environment [6]–[8]. At each time step, the agent perceives t ...
Diagnosing Self-Efficacy in Intelligent Tutoring Systems: An
... related to motivation, which controls the effort and persistence with which a student approaches a task [15]. Effort and persistence are themselves influenced by the belief the student has that she will be able to achieve a desired outcome [3]. Self-efficacy has been studied in many domains with sig ...
... related to motivation, which controls the effort and persistence with which a student approaches a task [15]. Effort and persistence are themselves influenced by the belief the student has that she will be able to achieve a desired outcome [3]. Self-efficacy has been studied in many domains with sig ...
Nuhoğlu, M., 2009, Simulation Modeling of Body Weight Dynamics
... a few modi cation areas in which our model diers from Hall's original model. Firstly, our model has some simpli cations that highlight the causality relationships more clearly, while maintaining the validity. Secondly, our model incorporates a hypothesized process called secondary oxidation to make ...
... a few modi cation areas in which our model diers from Hall's original model. Firstly, our model has some simpli cations that highlight the causality relationships more clearly, while maintaining the validity. Secondly, our model incorporates a hypothesized process called secondary oxidation to make ...
ppt - LaDiSpe - Politecnico di Torino
... repeat them to adapt to the implicit or explicit objectives In a broad sense, learning is the ability to adapt during life We know that most living organisms with a nervous system display some type of adaptation during life The ability to adapt quickly is crucial for autonomous robots that ope ...
... repeat them to adapt to the implicit or explicit objectives In a broad sense, learning is the ability to adapt during life We know that most living organisms with a nervous system display some type of adaptation during life The ability to adapt quickly is crucial for autonomous robots that ope ...
Nash Social Welfare in Multiagent Resource Allocation
... Multiagent resource allocation (MARA) is a loosely defined research area concerned with the study of mechanisms for distributing a set of resources among a group of agents—typically software agents with limited reasoning capabilities [3]. Each agent has their own preferences (e.g., a utility functio ...
... Multiagent resource allocation (MARA) is a loosely defined research area concerned with the study of mechanisms for distributing a set of resources among a group of agents—typically software agents with limited reasoning capabilities [3]. Each agent has their own preferences (e.g., a utility functio ...
Compositional Design of a Generic Design Agent
... the Generic Design Model GDM have been tested in different application domains, the architecture for a generic design agent described in this paper as yet has only been tested in the application domain of automated design of Internet agents. Therefore this application domain is used to illustrate ap ...
... the Generic Design Model GDM have been tested in different application domains, the architecture for a generic design agent described in this paper as yet has only been tested in the application domain of automated design of Internet agents. Therefore this application domain is used to illustrate ap ...
Lifelong Multi-Agent Path Finding for Online Pickup
... Past research efforts have concentrated mostly on a “one-shot” version of this problem, called the multi-agent path-finding (MAPF) problem, which has been studied in artificial intelligence, robotics, and operations research. In the MAPF problem, each agent has to move from its current location to i ...
... Past research efforts have concentrated mostly on a “one-shot” version of this problem, called the multi-agent path-finding (MAPF) problem, which has been studied in artificial intelligence, robotics, and operations research. In the MAPF problem, each agent has to move from its current location to i ...
Multi agent systems simulator in Common Lisp
... We can divide agents into types based on their agent function: Table agent A table agents’ agent function contains a table of percept sequences and actuators. Every history of percepts is mapped exactly to a list of actuators. While such an agent is perfect, it is unrealistic in any environment, exc ...
... We can divide agents into types based on their agent function: Table agent A table agents’ agent function contains a table of percept sequences and actuators. Every history of percepts is mapped exactly to a list of actuators. While such an agent is perfect, it is unrealistic in any environment, exc ...
query expansion using wordnet with a logical model - CiTIUS
... experiments were run. To simplify the test, the experiments only used the linguistic information recorded in WordNet as the source for expansion terms. The expansion experiments were tested against a subset of the TREC collection[13]. Each initial query in every experiment was generated automaticall ...
... experiments were run. To simplify the test, the experiments only used the linguistic information recorded in WordNet as the source for expansion terms. The expansion experiments were tested against a subset of the TREC collection[13]. Each initial query in every experiment was generated automaticall ...
Graph-based Diagnostic Medical Decision Support System
... what is causing symptoms when multiple possibilities exist. A physician will collect the evidence and attempt to discover all the possible causes. Beginning with the most likely causes, he or she will run tests to rule out possible causes until a diagnosis is made. A clinical decision support (CDS) ...
... what is causing symptoms when multiple possibilities exist. A physician will collect the evidence and attempt to discover all the possible causes. Beginning with the most likely causes, he or she will run tests to rule out possible causes until a diagnosis is made. A clinical decision support (CDS) ...
Slide 1
... • Intelligent agents promise to improve the interface in areas such as direct natural language processing and creating facial gestures ...
... • Intelligent agents promise to improve the interface in areas such as direct natural language processing and creating facial gestures ...
A suitable semantics for implicit and explicit belief
... set of explicit beliefs. The resulting semantics is both simple and flexible: implicit belief it typically modelled on normal frames for epistemic logic as a K45 or a KD45 modality, whereas different conditions imposed on the set of propositions of which the agents are aware allow us to capture var ...
... set of explicit beliefs. The resulting semantics is both simple and flexible: implicit belief it typically modelled on normal frames for epistemic logic as a K45 or a KD45 modality, whereas different conditions imposed on the set of propositions of which the agents are aware allow us to capture var ...
A Game-theoretic Machine Learning Approach for Revenue
... To overcome the above drawbacks, we propose a novel approach, which can naturally combine game theory and machine learning using a bilevel optimization framework, so as to simultaneously avoid the strong assumptions and handle the second-order effect. For ease of reference, we call the approach a g ...
... To overcome the above drawbacks, we propose a novel approach, which can naturally combine game theory and machine learning using a bilevel optimization framework, so as to simultaneously avoid the strong assumptions and handle the second-order effect. For ease of reference, we call the approach a g ...
Intelligent Agents - Department of Computer Science, Oxford
... term will lose all meaning (cf. “user friendly”). The definition presented here is adapted from [71]: An agent is a computer system that is situated in some environment, and that is capable of autonomous action in this environment in order to meet its design objectives. There are several points to n ...
... term will lose all meaning (cf. “user friendly”). The definition presented here is adapted from [71]: An agent is a computer system that is situated in some environment, and that is capable of autonomous action in this environment in order to meet its design objectives. There are several points to n ...
Multi-Agent Path Finding with Kinematic Constraints
... events v and v 0 indicating that event v must be scheduled between LB(e) and U B(e) time units before event v 0 . We add two additional vertices. XS represents the start event and therefore has edges annotated with the STN bounds [0, 0] to all vertices without incoming edges. Similarly, XF represent ...
... events v and v 0 indicating that event v must be scheduled between LB(e) and U B(e) time units before event v 0 . We add two additional vertices. XS represents the start event and therefore has edges annotated with the STN bounds [0, 0] to all vertices without incoming edges. Similarly, XF represent ...
Author`s personal copy
... of enacting them. We expect an EMDP agent to learn to skillfully cope with the environment using all the interactions at its disposal, and to demonstrate that it can use these skills for its own good by eventually enacting interactions that have positive values and avoiding interactions that have st ...
... of enacting them. We expect an EMDP agent to learn to skillfully cope with the environment using all the interactions at its disposal, and to demonstrate that it can use these skills for its own good by eventually enacting interactions that have positive values and avoiding interactions that have st ...
Predictive Control Algorithms Verification on the Laboratory Helicopter Model
... them, and other important issues like stability are mentioned in [3] or [4]. In this paper, we are engaged in a theoretical derivation of some predictive control methods based on the linear model of controlled system, and in preparing them for subsequent algorithmic design and verification on a real ...
... them, and other important issues like stability are mentioned in [3] or [4]. In this paper, we are engaged in a theoretical derivation of some predictive control methods based on the linear model of controlled system, and in preparing them for subsequent algorithmic design and verification on a real ...
MOTION DETECTION MECHANISMS
... The physical phenomenon ‘motion’ can easily be defined as an object’s change in position over time. An animal that can detect moving predators, prey, and mates, has a clear survival advantage and this evolutionary pressure has presumably led to the development of neural mechanisms sensitive to motio ...
... The physical phenomenon ‘motion’ can easily be defined as an object’s change in position over time. An animal that can detect moving predators, prey, and mates, has a clear survival advantage and this evolutionary pressure has presumably led to the development of neural mechanisms sensitive to motio ...
A Neural Schema Architecture for Autonomous Robots
... To enable the development and execution of complex behaviors in autonomous robots involving adaptation and learning, sophisticated software architectures are required. The neural schema architecture provides such a system, supporting the development and execution of complex behaviors, or schemas [3] ...
... To enable the development and execution of complex behaviors in autonomous robots involving adaptation and learning, sophisticated software architectures are required. The neural schema architecture provides such a system, supporting the development and execution of complex behaviors, or schemas [3] ...
Proceedings of the Seventh Int’l Conf. on Artificial Intelligence and Expert... San Francisco, November, 1995.
... The “Object-Oriented Simulation Module” (OOSM) of the RBOOS system was implemented in CLOS using a three-phase discrete event simulation [3] algorithm. The simulator was implemented as two main layers. The first layer consists of a general object-oriented discrete event simulator with classes define ...
... The “Object-Oriented Simulation Module” (OOSM) of the RBOOS system was implemented in CLOS using a three-phase discrete event simulation [3] algorithm. The simulator was implemented as two main layers. The first layer consists of a general object-oriented discrete event simulator with classes define ...