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Relational Object Maps for Mobile Robots
Relational Object Maps for Mobile Robots

Fuzzy Logic - Authentic Leadership Center
Fuzzy Logic - Authentic Leadership Center

... other applications, fuzzy logic or approaches have been used as a way of “naturalizing” or “humanizing” a process, such as categorization and research questionnaires. Still other approaches use fuzzy logic to help decision making and making sense of “dirty” or “noisy” data. We will briefly discuss s ...
Modelling Dynamic Causal Interactions with Bayesian Networks
Modelling Dynamic Causal Interactions with Bayesian Networks

... to increasing temporal indices. Therefore, a temporal noisy ANDgate can be modelled through a noisy MAX-gate by sorting the temporal values from past to future. Note that associating increasing intensity degrees to decreasing temporal indices, i.e. sorting the temporal values from future to past, a ...
A New Fixpoint Semantics for General Logic Programs Compared
A New Fixpoint Semantics for General Logic Programs Compared

... This result has been shown independently by [12] in the case where P is a propositional program. A propositional program like for example P2 = {p → p, ¬p → q} has two supported minimal models, {p} and {q}, which are both models of comp(P2 ), but only one well-supported model {q} (called a grounded m ...
Solving Everyday Physical Reasoning Problems by Analogy using
Solving Everyday Physical Reasoning Problems by Analogy using

... MAC/FAC on the problem sketch with low level visual properties removed, i.e. glyph orientations and relative sizes. For outcome problems the first retrieval is used. For DQA questions, the retrieval must also contain candidate inferences that causally constrain the goal quantity. Should the first re ...
Solving Everyday Physical Reasoning Problems
Solving Everyday Physical Reasoning Problems

... While most sketch understanding systems focus on recognition, nuSketch systems are based on the insight that recognition is not necessary in human-to-human sketching. The sketching Knowledge Entry Associate (sKEA) [12] is the first open-domain sketch understanding system. Anything that can be descri ...
Identifying and Accounting for Task-Dependent Bias in Crowdsourcing
Identifying and Accounting for Task-Dependent Bias in Crowdsourcing

Edo Bander
Edo Bander

... This research analyzes a CardiologyCategorical.xls data set. This data set contains 302 different instances of 14 different attribute. These attributes are: age, sex, chest pain type, blood pressure, cholesterol, blood sugar, resting heart rate, angina, peak, slope, colored vessels, thal and class. ...
Planning with graded fluents and actions - Carla Limongelli
Planning with graded fluents and actions - Carla Limongelli

Neural Global Pattern Similarity Underlies True and False Memories
Neural Global Pattern Similarity Underlies True and False Memories

State-Dependent Computation Using Coupled Recurrent Networks
State-Dependent Computation Using Coupled Recurrent Networks

... Mahowald, & Hepp, 1999; Maass, 2000), and so offers a form of signal restoration between computational stages sought by von Neumann (1958) in his early explorations of brainlike principles of computation. In theoretical models, the neurons that compose a winner-take-all (WTA) network are usually org ...
7. MODELING THE SOMATOTOPIC MAP 7.1 The Somatotopic Map
7. MODELING THE SOMATOTOPIC MAP 7.1 The Somatotopic Map

Name Nervous System Questions 1. When a neuron is at its resting
Name Nervous System Questions 1. When a neuron is at its resting

A Cognitive Architecture for a Humanoid Robot: A First Approach
A Cognitive Architecture for a Humanoid Robot: A First Approach

... II. OVERALL D ESIGN OF THE C OGNITIVE A RCHITECTURE A cognitive architecture for an intelligent robotic system is required to support fast perception, control and task execution on a low level as well as recognition and interpretation of complex contexts, planning of intrinsic tasks, and learning of ...
On the Structural Robustness of Evolutionary Models of Cooperation
On the Structural Robustness of Evolutionary Models of Cooperation

... defects, in which case it switches to defection forever. Linster [17] attributed the success of GRIM over TFT to the fact that GRIM is able to exploit poor strategies while TFT is not. Linster’s investigation was truly remarkable at its time, but technology has advanced considerably since then, and ...
A Computational Intelligence Approach to Modelling Interstate Conflict
A Computational Intelligence Approach to Modelling Interstate Conflict

... Militarised Interstate Disputes (MID) as a set of interactions between or among states that can result in the actual use, display, or threat of using military force in an explicit way [2]. A further contribution that has seen advances in the quantitative study of interstate conflict has been the ado ...
Contraction Properties of VLSI Cooperative Competitive Neural
Contraction Properties of VLSI Cooperative Competitive Neural

... across all areas in the cortex [1]. It has been argued that a good candidate model for a canonical micro-circuit, potentially used as a general purpose cortical computational unit in the cortices, is the soft Winner-Take-All (WTA) circuit [1], or the more general class of Cooperative Competitive Net ...
Mining Classification Rules from Database by Using Artificial Neural
Mining Classification Rules from Database by Using Artificial Neural

... according to fitness. An elitist strategy is then used whereby a subset of the top chromosomes is selected for inclusion in the next generation. Crossover and mutation are then performed on these chromosomes to create the rest of the next population. The chromosome is then easily converted into IF…T ...
Learning Action Models for Multi-Agent Planning
Learning Action Models for Multi-Agent Planning

Computational rationality: A converging paradigm
Computational rationality: A converging paradigm

A Neural Mass Model to Simulate Different Rhythms in a Cortical
A Neural Mass Model to Simulate Different Rhythms in a Cortical

... action potentials coming from other regions. Inputs to the other two populations have only a scanty effect on model dynamics, and hence have been neglected. The output of the model is represented by the membrane potential of pyramidal cells. Compared with the model described in our previous work [8], ...
Philosophers are Mortal: Inferring the Truth of Unseen Facts
Philosophers are Mortal: Inferring the Truth of Unseen Facts

... a member of the database, with an informative degree of confidence. Since often the facts in these databases are devoid of context, we refine our notion of truth to reflect whether we would assume a fact to be true without evidence to the contrary. In this vein, we can further refine our task as det ...
choosing the greater of two goods: neural currencies for valuation
choosing the greater of two goods: neural currencies for valuation

... available options. The nascent field of neuroeconomics has set itself the ambitious goal of understanding the brain mechanisms that are responsible for these evaluative processes. A series of recent neurophysiological studies in monkeys has begun to address this challenge using novel methods to mani ...
GENERAL CONCLUSIONS
GENERAL CONCLUSIONS

... majority of LNs (heterogeneous LNs), which densely innervate one particular glomerulus and diffusely branch in other glomeruli. Its transmitter could be histamine, which has been shown to act as an inhibitory transmitter in the honeybee AL (CHAPTER II). This specific network connects glomeruli with ...
Predicting voluntary movements from motor cortical activity with
Predicting voluntary movements from motor cortical activity with

... This so-called lateral inhibition reduces input correlation and thereby improves classification performance [33], [36]. In the association layer there are two excitatory association neuron (ANe) populations that receive input from the projection neurons via plastic synapses. After training (outline ...
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Neural modeling fields

Neural modeling field (NMF) is a mathematical framework for machine learning which combines ideas from neural networks, fuzzy logic, and model based recognition. It has also been referred to as modeling fields, modeling fields theory (MFT), Maximum likelihood artificial neural networks (MLANS).This framework has been developed by Leonid Perlovsky at the AFRL. NMF is interpreted as a mathematical description of mind’s mechanisms, including concepts, emotions, instincts, imagination, thinking, and understanding. NMF is a multi-level, hetero-hierarchical system. At each level in NMF there are concept-models encapsulating the knowledge; they generate so-called top-down signals, interacting with input, bottom-up signals. These interactions are governed by dynamic equations, which drive concept-model learning, adaptation, and formation of new concept-models for better correspondence to the input, bottom-up signals.
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