Contributions to Deep Learning Models - RiuNet
... Error rate (\%) on the MNIST test set for both clean and noisy images using different regularization schemes and varying the number of labeled samples used in the fine-tuning. . . . . . . . . . . . . . . . . . Effect of applying MSR to different layers of the network. Error rate (\%) on the MNIST te ...
... Error rate (\%) on the MNIST test set for both clean and noisy images using different regularization schemes and varying the number of labeled samples used in the fine-tuning. . . . . . . . . . . . . . . . . . Effect of applying MSR to different layers of the network. Error rate (\%) on the MNIST te ...
querying description logic knowledge bases
... defined syntax and semantics. A Description Logic allows for the specification of concepts (also known as classes), individuals (also known as objects) that are instances of these concepts, and roles (also known as properties) that are interpreted as pairs of individuals that are related by the role ...
... defined syntax and semantics. A Description Logic allows for the specification of concepts (also known as classes), individuals (also known as objects) that are instances of these concepts, and roles (also known as properties) that are interpreted as pairs of individuals that are related by the role ...
The Role of Subjectivity in Intelligent Systems Communication and
... the tools used by a subject to perform activities in a determinate context (Bernat 2011). Seen from the activity theory perspective Agency is in fact liable to change in response to new contextual developments, feature that is important in software agent communication activities. In this context, th ...
... the tools used by a subject to perform activities in a determinate context (Bernat 2011). Seen from the activity theory perspective Agency is in fact liable to change in response to new contextual developments, feature that is important in software agent communication activities. In this context, th ...
Financial Time Series Forecasting Using Improved Wavelet Neural
... Hybrid models do not always give better performance than individual models. For instance, [91] presents a Neural Net-PMRS hybrid model for forecasting exchange rates. The model uses a traditional multilayer neural network as predictor, but rather than using the last n observations for prediction, th ...
... Hybrid models do not always give better performance than individual models. For instance, [91] presents a Neural Net-PMRS hybrid model for forecasting exchange rates. The model uses a traditional multilayer neural network as predictor, but rather than using the last n observations for prediction, th ...
Intelligence by Design: Principles of Modularity and Coordination for
... All intelligence relies on search — for example, the search for an intelligent agent’s next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dis ...
... All intelligence relies on search — for example, the search for an intelligent agent’s next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dis ...
Eliciting Single-Peaked Preferences Using Comparison Queries
... on its own). First, the elicitor provides the agent with a systematic way of assessing its preferences: all that the agent needs to do is answer simple queries. Second, and perhaps more importantly, once the elicitor has elicited the preferences of some agents, the elicitor will have some understand ...
... on its own). First, the elicitor provides the agent with a systematic way of assessing its preferences: all that the agent needs to do is answer simple queries. Second, and perhaps more importantly, once the elicitor has elicited the preferences of some agents, the elicitor will have some understand ...
Intelligence by Design - Department of Computer Science
... All intelligence relies on search — for example, the search for an intelligent agent’s next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dis ...
... All intelligence relies on search — for example, the search for an intelligent agent’s next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dis ...
A Computational Model of Belief - Rochester CS
... are incompatible with a theory of how belief in one sentence (or proposition) is related to belief in another, only that they do not themselves include such a theory. Another model, the “possible worlds” model, has more structure. In this model, the set of sentences that a person believes can’t be a ...
... are incompatible with a theory of how belief in one sentence (or proposition) is related to belief in another, only that they do not themselves include such a theory. Another model, the “possible worlds” model, has more structure. In this model, the set of sentences that a person believes can’t be a ...
The DL-Lite Family - Dipartimento di Informatica e Sistemistica
... of constructs expressible in the knowledge base does not pose particular difficulties to TBox reasoning. Indeed, in spite of the simplicity of DL-Litecore TBoxes, the ability of taking TBox knowledge into account during the process of answering (unions of) conjunctive queries goes beyond the two-var ...
... of constructs expressible in the knowledge base does not pose particular difficulties to TBox reasoning. Indeed, in spite of the simplicity of DL-Litecore TBoxes, the ability of taking TBox knowledge into account during the process of answering (unions of) conjunctive queries goes beyond the two-var ...
Dissection of Genetic Factors Modulating Fetal Growth in
... one chromosome with a length of 1.2 M and an average marker density for the variance component analyses of 0.02927 M. LRT significance thresholds for a ¼ 0.05 and a ¼ 0.0001 were 10.5 and 24. The variance component approach used to model a random QTL effect (Perez-Enciso and Misztal 2004) further co ...
... one chromosome with a length of 1.2 M and an average marker density for the variance component analyses of 0.02927 M. LRT significance thresholds for a ¼ 0.05 and a ¼ 0.0001 were 10.5 and 24. The variance component approach used to model a random QTL effect (Perez-Enciso and Misztal 2004) further co ...
Aalborg Universitet
... the goal of arriving at the true diagnosis or conclusion of a given problem, but also a desire to do so as efficiently as possible. In layman’s terms, the faster (or cheaper) we arrive at the proper conclusion, the better. But decision theoretic troubleshooting goes further than that because it esta ...
... the goal of arriving at the true diagnosis or conclusion of a given problem, but also a desire to do so as efficiently as possible. In layman’s terms, the faster (or cheaper) we arrive at the proper conclusion, the better. But decision theoretic troubleshooting goes further than that because it esta ...
Intelligent Distributed Agent Based Architecture
... The new approach to coordination was inspired by social networks, as observed in higher mammalian societies. Two social relationships were explored, namely kinship and trust. Coordination is achieved through team selection. Using characteristics of social networks, such as learning and the ability t ...
... The new approach to coordination was inspired by social networks, as observed in higher mammalian societies. Two social relationships were explored, namely kinship and trust. Coordination is achieved through team selection. Using characteristics of social networks, such as learning and the ability t ...
Contrast-dependence of surround suppression in
... and 80% contrast); low contrast values were generally chosen to be those eliciting b 50% of the maximum response in the cell's contrastresponse function, but still eliciting a reliable response (at least 2 SD greater than the spontaneous firing rate; typically between 4% and 30%; the cell in Fig. 2c ...
... and 80% contrast); low contrast values were generally chosen to be those eliciting b 50% of the maximum response in the cell's contrastresponse function, but still eliciting a reliable response (at least 2 SD greater than the spontaneous firing rate; typically between 4% and 30%; the cell in Fig. 2c ...
Automated Negotiations Among Autonomous Agents
... Dissertation Overview . . . . . . . . . . . . . . . . . . . . . . . . . . ...
... Dissertation Overview . . . . . . . . . . . . . . . . . . . . . . . . . . ...
Gerenciamento Autônomo de Redes na Internet do
... network controlling mechanisms. Deploying such autonomous and rational entities in the network can improve its behavior in the presence of very dynamic and complex control scenarios. Unfortunately, building agent-based mechanisms for networks is not an easy task. The main difficulty is to create con ...
... network controlling mechanisms. Deploying such autonomous and rational entities in the network can improve its behavior in the presence of very dynamic and complex control scenarios. Unfortunately, building agent-based mechanisms for networks is not an easy task. The main difficulty is to create con ...
CS 561a: Introduction to Artificial Intelligence
... • Agents are autonomous, that is, they act on behalf of the user • Agents contain some level of intelligence, from fixed rules to learning engines that allow them to adapt to changes in the environment • Agents don‘t only act reactively (被動地因應改變), but sometimes also proactively ( 主動地改變) ...
... • Agents are autonomous, that is, they act on behalf of the user • Agents contain some level of intelligence, from fixed rules to learning engines that allow them to adapt to changes in the environment • Agents don‘t only act reactively (被動地因應改變), but sometimes also proactively ( 主動地改變) ...
Artificial Intelligence
... agent simply by T ELLing it what it needs to know. The agent’s initial program, before it starts to receive percepts, is built by adding one by one the sentences that represent the designer’s knowledge of the environment. Designing the representation language to make it easy to express this knowledg ...
... agent simply by T ELLing it what it needs to know. The agent’s initial program, before it starts to receive percepts, is built by adding one by one the sentences that represent the designer’s knowledge of the environment. Designing the representation language to make it easy to express this knowledg ...
Negotiating Socially Optimal Allocations of Resources: An Overview
... are, in principle, also applicable in the distributed case, but research in this area has not yet reached the same level of maturity as for combinatorial auctions. An important argument against centralised approaches is that it may be difficult to find an agent that could assume the role of an “auc ...
... are, in principle, also applicable in the distributed case, but research in this area has not yet reached the same level of maturity as for combinatorial auctions. An important argument against centralised approaches is that it may be difficult to find an agent that could assume the role of an “auc ...
Osmand Christian - XY Home
... As much as agents help tackling interoperability problems, they also enable negotiation for services and resources. Agents are typically in heterogeneous systems with inherently distributed data, their own control and resources. Interactions become a core part of these agents, especially at run-time ...
... As much as agents help tackling interoperability problems, they also enable negotiation for services and resources. Agents are typically in heterogeneous systems with inherently distributed data, their own control and resources. Interactions become a core part of these agents, especially at run-time ...
pre-print - School of Computer Science, University of Birmingham.
... different varieties of simulative and non-simulative meta-reasoning carefully, as some varieties of non-simulative reasoning are not that different from some varieties of Simulative Reasoning. The other half of the chapter yokes Simulative Reasoning to a different and rather radical proposal about ...
... different varieties of simulative and non-simulative meta-reasoning carefully, as some varieties of non-simulative reasoning are not that different from some varieties of Simulative Reasoning. The other half of the chapter yokes Simulative Reasoning to a different and rather radical proposal about ...
teză de doctorat - AI-MAS
... artificial agent behavior. Virtual characters acting in an intelligent manner based on their goals and desires as opposed to standing still, waiting around for the user and interacting based on pre-scripted dialog trees brings a great deal of depth to the experience. Evolving virtual worlds are by f ...
... artificial agent behavior. Virtual characters acting in an intelligent manner based on their goals and desires as opposed to standing still, waiting around for the user and interacting based on pre-scripted dialog trees brings a great deal of depth to the experience. Evolving virtual worlds are by f ...
“left or right” Decision-making beyond
... How do we make decisions? A comprehensive answer to this multifaceted question cannot be given within the scope of one single scientific discipline. Fields from philosophy to economic sciences aim to shed light on particular aspects of decision-making, approaching the topic from different perspectiv ...
... How do we make decisions? A comprehensive answer to this multifaceted question cannot be given within the scope of one single scientific discipline. Fields from philosophy to economic sciences aim to shed light on particular aspects of decision-making, approaching the topic from different perspectiv ...
cortical limbic system: a computational model. PhD thesis. htt
... The striatum is a major input structure of the basal ganglia and is a target structure of dopaminergic neurons which originate from the mid brain. These dopaminergic neurons release dopamine which is known to exert modulatory influences on the striatal projections. Action selection and control are i ...
... The striatum is a major input structure of the basal ganglia and is a target structure of dopaminergic neurons which originate from the mid brain. These dopaminergic neurons release dopamine which is known to exert modulatory influences on the striatal projections. Action selection and control are i ...
Intrusion detection using clustering
... In [12] modified K-mean clustering algorithm called KD clustering has been used for intrusion detection. In this clustering algorithm, Set S is initialized to null where S is the collection of clusters. For allocation of the data points, checked , if S is null then a new cluster is built and added i ...
... In [12] modified K-mean clustering algorithm called KD clustering has been used for intrusion detection. In this clustering algorithm, Set S is initialized to null where S is the collection of clusters. For allocation of the data points, checked , if S is null then a new cluster is built and added i ...
Integrating Planning, Execution and Learning to Improve Plan
... Figure 3. Execution algorithm for domains with dead-ends. the-shelf spirit of the architecture allows pela to acquire other useful execution information, such as the actions durations (Lanchas et al., 2007). 3.1. Learning rules about the actions performance For each action a ∈ A, pela learns a model ...
... Figure 3. Execution algorithm for domains with dead-ends. the-shelf spirit of the architecture allows pela to acquire other useful execution information, such as the actions durations (Lanchas et al., 2007). 3.1. Learning rules about the actions performance For each action a ∈ A, pela learns a model ...