Modeling Dyadic Data with Binary Latent Factors
... grouping the rows and (independently or simultaneously) the columns[6, 13, 9]. The modelling assumption in such a case is that movies come in K types and viewers in L types and that knowing the type of movie and type of viewer is sufficient to predict the response. Clustering or mixture models are q ...
... grouping the rows and (independently or simultaneously) the columns[6, 13, 9]. The modelling assumption in such a case is that movies come in K types and viewers in L types and that knowing the type of movie and type of viewer is sufficient to predict the response. Clustering or mixture models are q ...
Class Overview and Intro to AI
... • The right thing: which is expected to maximize goal achievement, given the available information • The rational-agent approach has two advantages – It’s more general than the “laws of thought” because correct inference is just one of several possible mechanisms for achieving rationality – Second , ...
... • The right thing: which is expected to maximize goal achievement, given the available information • The rational-agent approach has two advantages – It’s more general than the “laws of thought” because correct inference is just one of several possible mechanisms for achieving rationality – Second , ...
Note 1: introduction
... • Knowing about the current state of the environment is not always enough to decide what to do • Agent needs some sort of goal information also • Agent a program combines of this with information about the results of possible actions (the same information as was used to update internal state in the ...
... • Knowing about the current state of the environment is not always enough to decide what to do • Agent needs some sort of goal information also • Agent a program combines of this with information about the results of possible actions (the same information as was used to update internal state in the ...
Using Bayesian Networks and Simulation for Data
... show how to get the BN to generate quantified risk predictions and other useful functions like simulation, backward reasoning and what-if-analysis. Once the topology of a BN has been constructed we need to add node probability tables (NPT) to it, which represent the quantitative specification of loc ...
... show how to get the BN to generate quantified risk predictions and other useful functions like simulation, backward reasoning and what-if-analysis. Once the topology of a BN has been constructed we need to add node probability tables (NPT) to it, which represent the quantitative specification of loc ...
Policy Communication for Coordination with Unknown Teammates
... agent acting within the same environment. Analogously, the refinement of predicted action probabilities and, consequently, an improved policy for a coordinating agent is desirable for ad hoc teams. Whereas the broadcast of the intention of pursuing a goal addresses multiple state-action pairs within ...
... agent acting within the same environment. Analogously, the refinement of predicted action probabilities and, consequently, an improved policy for a coordinating agent is desirable for ad hoc teams. Whereas the broadcast of the intention of pursuing a goal addresses multiple state-action pairs within ...
Towards Real-time Probabilistic Risk Assessment by
... contained 10 news stories and, depending on the frequency of newsworthy events, there would be a number of new stories and a number already seen by our application in previous data collection runs. For each news story we save the title, description, Globally Unique IDentifier (GUID) and last publica ...
... contained 10 news stories and, depending on the frequency of newsworthy events, there would be a number of new stories and a number already seen by our application in previous data collection runs. For each news story we save the title, description, Globally Unique IDentifier (GUID) and last publica ...
intelligent agent
... Agent Definition (1) • An agent is an entity which is: – Situated in some environment. – Autonomous, in the sense that it can act without direct intervention from humans or other software processes, and controls over its own actions and internal state. – Flexible which means: • Responsive (reactive ...
... Agent Definition (1) • An agent is an entity which is: – Situated in some environment. – Autonomous, in the sense that it can act without direct intervention from humans or other software processes, and controls over its own actions and internal state. – Flexible which means: • Responsive (reactive ...
Intelligent Agents - University of Washington
... • Key idea: Occam’s Rasor: We want the simplest possible system that generalizes well (given a choice between two systems that perform equally on a given data set, we choose the simpler one) ...
... • Key idea: Occam’s Rasor: We want the simplest possible system that generalizes well (given a choice between two systems that perform equally on a given data set, we choose the simpler one) ...
Model Checking of Hybrid Systems via Satisfiability Modulo Theories
... Complex embedded systems are increasingly present in our daily lives, whenever a computer-based system interacts with some physical plant or environment. Some application domains of interest are industrial production, automotive, railways, and aerospace. The key feature of such complex system, often ...
... Complex embedded systems are increasingly present in our daily lives, whenever a computer-based system interacts with some physical plant or environment. Some application domains of interest are industrial production, automotive, railways, and aerospace. The key feature of such complex system, often ...
Swarm intelligence (SI) is the collective
... an ant colony. ACO methods are useful in problems that need to find paths to goals. Artificial 'ants'—simulation agents—locate optimal solutions by moving through a parameter space representing all possible solutions. Real ants lay down pheromones directing each other to resources while exploring th ...
... an ant colony. ACO methods are useful in problems that need to find paths to goals. Artificial 'ants'—simulation agents—locate optimal solutions by moving through a parameter space representing all possible solutions. Real ants lay down pheromones directing each other to resources while exploring th ...
PANGEA: A New Platform for Developing Virtual Organizations of
... emerged in response to this idea; they include a set of agents with roles and norms that determine their behaviour, and represent a place where these new capabilities will assume a critical role. Possible organizational topologies and aspects such as communication and coordination mechanisms determi ...
... emerged in response to this idea; they include a set of agents with roles and norms that determine their behaviour, and represent a place where these new capabilities will assume a critical role. Possible organizational topologies and aspects such as communication and coordination mechanisms determi ...
Optimal decision-making theories: linking neurobiology with behaviour
... can be parameterized to implement an optimal test called the sequential probability ratio test (SPRT) [19], and then they predict exactly the same error rate (ER) and reaction time (RT) distributions. Thus, if one model that implements SPRT fits behavioural data, all other models (including those on ...
... can be parameterized to implement an optimal test called the sequential probability ratio test (SPRT) [19], and then they predict exactly the same error rate (ER) and reaction time (RT) distributions. Thus, if one model that implements SPRT fits behavioural data, all other models (including those on ...
Trends in Cognitive Sciences 2007 Bogacz
... can be parameterized to implement an optimal test called the sequential probability ratio test (SPRT) [19], and then they predict exactly the same error rate (ER) and reaction time (RT) distributions. Thus, if one model that implements SPRT fits behavioural data, all other models (including those on ...
... can be parameterized to implement an optimal test called the sequential probability ratio test (SPRT) [19], and then they predict exactly the same error rate (ER) and reaction time (RT) distributions. Thus, if one model that implements SPRT fits behavioural data, all other models (including those on ...
Men Behaving Appropriately: Brian MacNamee ; Simon Dobbyn
... technique of role-passing allows intelligent agents to take on different roles depending on the situation in which they are found. This section will explore the technique of role-passing, examining its advantages and how it complements LOD techniques. Role-passing operates by using a schedule to lay ...
... technique of role-passing allows intelligent agents to take on different roles depending on the situation in which they are found. This section will explore the technique of role-passing, examining its advantages and how it complements LOD techniques. Role-passing operates by using a schedule to lay ...
Flexible sequence learning in a SOM model of the mirror system
... Figure 3: Correct activation/non-activation. Dark bars indicate the proportion of cases in which presenting the first element of a sequence correctly triggered the sequence. Light bars indicate the proportion of the cases that correctly trigger which correctly remain silent if the first element pres ...
... Figure 3: Correct activation/non-activation. Dark bars indicate the proportion of cases in which presenting the first element of a sequence correctly triggered the sequence. Light bars indicate the proportion of the cases that correctly trigger which correctly remain silent if the first element pres ...
View PDF - CiteSeerX
... domain, which has lead to the appearance of the MAS approach. The rst attempts to solve problems cooperatively can be found in the seventies [FERB91a]. One of the rst of these attempts was the HEARSAY-II project [ERMA80], a speech understanding system which introduced the Blackboard model [ENGE88] ...
... domain, which has lead to the appearance of the MAS approach. The rst attempts to solve problems cooperatively can be found in the seventies [FERB91a]. One of the rst of these attempts was the HEARSAY-II project [ERMA80], a speech understanding system which introduced the Blackboard model [ENGE88] ...
Survey and Evaluation of Agent Oriented Software Engineering
... a useful paradigm in software engineering which has been referred to as agent-oriented software engineering (AOSE). The core phases of software engineering are analysis and design phases, these two phases are mostly affected with evolution of software engineering paradigm. We attested a massive deve ...
... a useful paradigm in software engineering which has been referred to as agent-oriented software engineering (AOSE). The core phases of software engineering are analysis and design phases, these two phases are mostly affected with evolution of software engineering paradigm. We attested a massive deve ...
Paper Title
... can be successful only if the individual models are highly accurate in terms of precision (thus coinciding predictions will more often mean error correction), we applied a boosting strategy to improve the precision of the three learning models at the cost of somewhat lower recall. Boosting was intro ...
... can be successful only if the individual models are highly accurate in terms of precision (thus coinciding predictions will more often mean error correction), we applied a boosting strategy to improve the precision of the three learning models at the cost of somewhat lower recall. Boosting was intro ...
Revising Domain Knowledge with Cross
... Table 1. Analogy given to students. All students saw the non-italicized text; only students in the analogy condition saw the italicized text. The Earth is round. Day changes to night because the Earth turns around its axis. The earth is moving just like gyros turns around on the vertical spit while ...
... Table 1. Analogy given to students. All students saw the non-italicized text; only students in the analogy condition saw the italicized text. The Earth is round. Day changes to night because the Earth turns around its axis. The earth is moving just like gyros turns around on the vertical spit while ...
Agent Computing and Situation Aware
... their relations are modeled. Different notions of strong and weak agency are presented at (Wooldridge and Jennings, 1995). (Velde and Perram, 1996) distinguished big and small agents. To apply agent computing with intelligent multimedia some specific roles and models have to be presented for agents. ...
... their relations are modeled. Different notions of strong and weak agency are presented at (Wooldridge and Jennings, 1995). (Velde and Perram, 1996) distinguished big and small agents. To apply agent computing with intelligent multimedia some specific roles and models have to be presented for agents. ...
Towards Adversarial Reasoning in Statistical Relational Domains
... To summarize, this optimization problem finds actions as to maximize the utility of agent s, assuming that agent o will respond with an action ao that has higher utility than reference action a0o . If most of the opponent’s high-utility actions are similar, then this could be a reasonable approximat ...
... To summarize, this optimization problem finds actions as to maximize the utility of agent s, assuming that agent o will respond with an action ao that has higher utility than reference action a0o . If most of the opponent’s high-utility actions are similar, then this could be a reasonable approximat ...
A bayesian computer vision system for modeling human interactions
... potentially dangerous situations. Moreover, all the processing modules need to be integrated in a consistent way. Our approach to modeling person-to-person interactions is to use supervised statistical machine learning techniques to teach the system to recognize normal single-person behaviors and co ...
... potentially dangerous situations. Moreover, all the processing modules need to be integrated in a consistent way. Our approach to modeling person-to-person interactions is to use supervised statistical machine learning techniques to teach the system to recognize normal single-person behaviors and co ...
Coupled Noisy Spiking Neurons as Velocity-Controlled
... these step sizes were sufficiently small. As our simulations often comA quantitative measure of the phase of the network oscillators was prised hundreds of cells (15,000 in the largest simulation) and were desired, but translating the state of a neuron into the corresponding up to 320 s long, it was ...
... these step sizes were sufficiently small. As our simulations often comA quantitative measure of the phase of the network oscillators was prised hundreds of cells (15,000 in the largest simulation) and were desired, but translating the state of a neuron into the corresponding up to 320 s long, it was ...