NRC 39221
... other features. Irrelevant features are not useful for classification, either when considered alone or when combined with other features. We believe that primary features are often context-sensitive. That is, they may be useful for classification when considered in isolation, but the learning algori ...
... other features. Irrelevant features are not useful for classification, either when considered alone or when combined with other features. We believe that primary features are often context-sensitive. That is, they may be useful for classification when considered in isolation, but the learning algori ...
Mapping Between Agent Architectures and Brain Organization
... In Section 2 we discussed modularity in mammalian brains. Using that terminology, we consider the skill modules of CAA to correspond roughly to functional modularity, particularly in the neocortex, and perhaps to some extent to temporal modularity. However, there is no direct correlation between bra ...
... In Section 2 we discussed modularity in mammalian brains. Using that terminology, we consider the skill modules of CAA to correspond roughly to functional modularity, particularly in the neocortex, and perhaps to some extent to temporal modularity. However, there is no direct correlation between bra ...
Learning Long-term Planning in Basketball Using
... they have the ball, dribble, pass or shoot. These microactions operate at the millisecond scale, whereas their macrogoals, such as ”maneuver behind these 2 defenders towards the basket”, span multiple seconds. Figure 1 depicts an example from a professional basketball game, where the player must mak ...
... they have the ball, dribble, pass or shoot. These microactions operate at the millisecond scale, whereas their macrogoals, such as ”maneuver behind these 2 defenders towards the basket”, span multiple seconds. Figure 1 depicts an example from a professional basketball game, where the player must mak ...
A reinforcement learning model of joy, distress, hope and fear.
... anticipation of loss or gain. Further, we propose that joy/distress is a signal similar to the error signal. We present agent-based simulation experiments that show that this model replicates psychological and behavioral dynamics of emotion. This work distinguishes itself by assessing the dynamics o ...
... anticipation of loss or gain. Further, we propose that joy/distress is a signal similar to the error signal. We present agent-based simulation experiments that show that this model replicates psychological and behavioral dynamics of emotion. This work distinguishes itself by assessing the dynamics o ...
Chapter 1: Introduction to AI
... Can Computers Learn and Adapt ? • Learning and Adaptation – consider a computer learning to drive on the freeway – we could teach it lots of rules about what to do – or we could let it drive and steer it back on course when it heads for the embankment • systems like this are under development (e.g. ...
... Can Computers Learn and Adapt ? • Learning and Adaptation – consider a computer learning to drive on the freeway – we could teach it lots of rules about what to do – or we could let it drive and steer it back on course when it heads for the embankment • systems like this are under development (e.g. ...
Reports of the AAAI 2010 Conference Workshops
... But what is fun? We seem to know it when we see it, but fun is also highly subjective. Can we computationally model fun? Can intelligent systems learn and utilize models of fun, player preferences, storytelling, and so on, to affect human experiences? If so, what would this enable with respect to in ...
... But what is fun? We seem to know it when we see it, but fun is also highly subjective. Can we computationally model fun? Can intelligent systems learn and utilize models of fun, player preferences, storytelling, and so on, to affect human experiences? If so, what would this enable with respect to in ...
Supervised and unsupervised learning.
... strategy q : X → D which would be optimal with respect to certain criterion. Bayesian decision theory requires complete statistical information pXK ( x, k ) of the object of interest to be known, and a suitable penalty function W : K × D → R must be provided. Non-Bayesian decision theory studies tas ...
... strategy q : X → D which would be optimal with respect to certain criterion. Bayesian decision theory requires complete statistical information pXK ( x, k ) of the object of interest to be known, and a suitable penalty function W : K × D → R must be provided. Non-Bayesian decision theory studies tas ...
Probabilistic Inductive Logic Programming
... trees. These trees directly correspond to the proof-trees we talk about. Even ...
... trees. These trees directly correspond to the proof-trees we talk about. Even ...
Uluslararası İnsan Bilimleri Dergisi
... Technology is a constantly developing and changing aspect of learning. Over the last 30 years of educational revolution, it may be observed that mobile operating systems help users to access information 24/7 through Intelligent Personal Assistants (IPAs) working within Artificial Intelligence (AI). ...
... Technology is a constantly developing and changing aspect of learning. Over the last 30 years of educational revolution, it may be observed that mobile operating systems help users to access information 24/7 through Intelligent Personal Assistants (IPAs) working within Artificial Intelligence (AI). ...
Learning Concepts by Interaction
... makes sense, then, to ask how this knowledge is acquired by humans and how might it be acquired by machines. I focus on the origins of conceptual knowledge, the earliest distinctions and classes, the first efforts to carve the world at its joints. One reason is just the desire to get to the bottom o ...
... makes sense, then, to ask how this knowledge is acquired by humans and how might it be acquired by machines. I focus on the origins of conceptual knowledge, the earliest distinctions and classes, the first efforts to carve the world at its joints. One reason is just the desire to get to the bottom o ...
Proceedings of 2014 BMI the Third International Conference on
... orientation, which places important constraints on perceptual learning theories, many of which assume that perceptual learning occurs in the early visual areas that are retinotopic and orientation selective. However, we created new experimental paradigms to demonstrate that location and orientation ...
... orientation, which places important constraints on perceptual learning theories, many of which assume that perceptual learning occurs in the early visual areas that are retinotopic and orientation selective. However, we created new experimental paradigms to demonstrate that location and orientation ...
Catastrophic Forgetting in Connectionist Networks: Causes
... Cohen1 and Ratcliff2. They suggested that there might be a fundamental limitation to this type of distributed architecture, in the same way that Minsky and Papert3 had shown twenty years before that there were certain fundamental limitations to what a perceptron4,5 could do. They observed that under ...
... Cohen1 and Ratcliff2. They suggested that there might be a fundamental limitation to this type of distributed architecture, in the same way that Minsky and Papert3 had shown twenty years before that there were certain fundamental limitations to what a perceptron4,5 could do. They observed that under ...
Learning Abductive Reasoning Using Random Examples
... depend polynomially on the number of attributes n, probability of observing the condition µ, and degree of approximation desired. As with PAC-learning, we will actually obtain running times that only depend polynomially on log 1/δ rather than 1/δ (but in general we might be satisfied with the latt ...
... depend polynomially on the number of attributes n, probability of observing the condition µ, and degree of approximation desired. As with PAC-learning, we will actually obtain running times that only depend polynomially on log 1/δ rather than 1/δ (but in general we might be satisfied with the latt ...
Auditory Nerve Stochasticity Impedes Category Learning: the Role
... average values reported by [13] for male speakers. It can be seen that the generated vowel transforms are in line with the vowel distribution clouds produced from natural speech of a single speaker [14]. All transforms were checked by human subjects to ensure that they were recognisable as either an ...
... average values reported by [13] for male speakers. It can be seen that the generated vowel transforms are in line with the vowel distribution clouds produced from natural speech of a single speaker [14]. All transforms were checked by human subjects to ensure that they were recognisable as either an ...
The challenge of complexity for cognitive systems
... might be only partially observable and as a consequence, the outcome of actions cannot be predicted with certainty. Another cause for uncertain outcome of actions can be that the environment is nondeterministic due to uncontrollable factors (e.g., gambles), unpredictable changes (e.g., weather), or ...
... might be only partially observable and as a consequence, the outcome of actions cannot be predicted with certainty. Another cause for uncertain outcome of actions can be that the environment is nondeterministic due to uncontrollable factors (e.g., gambles), unpredictable changes (e.g., weather), or ...
Online Bayesian Passive-Aggressive Learning
... some deterministic objective function. This may lead to some inconvenience. For example, a single large-margin model is often less than sufficient in describing complex data, such as those with rich underlying structures. On the other hand, Bayesian methods enjoy the great flexibility in describing ...
... some deterministic objective function. This may lead to some inconvenience. For example, a single large-margin model is often less than sufficient in describing complex data, such as those with rich underlying structures. On the other hand, Bayesian methods enjoy the great flexibility in describing ...
Research Trends in Technology-based Learning from 2000 to 2009
... longer limited to the traditional environment. Communication technologies such as the Internet, digital programs and systems, Personal Digital Assistants (PDA), and simulation games have been integrated into instruction to support learning. As a result, technology-based learning refers to the proces ...
... longer limited to the traditional environment. Communication technologies such as the Internet, digital programs and systems, Personal Digital Assistants (PDA), and simulation games have been integrated into instruction to support learning. As a result, technology-based learning refers to the proces ...
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... Menlo Park, CA – May 19, 2011. Each year AAAI recognizes a small number of distinguished AI scientists for their outstanding contributions to the theory or practice of AI by electing them AAAI Fe ...
... Menlo Park, CA – May 19, 2011. Each year AAAI recognizes a small number of distinguished AI scientists for their outstanding contributions to the theory or practice of AI by electing them AAAI Fe ...
Neural Networks and Evolutionary Computation
... been employed as tools for escaping from local error minima of backpropagation–trained networks, and in [35] these concepts have been used to enable unsupervised learning networks to change their structure adaptively. A survey of formal models for describing the dynamics of genotype– phenotype evolu ...
... been employed as tools for escaping from local error minima of backpropagation–trained networks, and in [35] these concepts have been used to enable unsupervised learning networks to change their structure adaptively. A survey of formal models for describing the dynamics of genotype– phenotype evolu ...
Computational Creativity
... Hiller and Isaacson (1958) work, on the ILLIAC computer, is the best known pioneering work in computer music. Their chief result is the Illiac Suite, a string quartet composed following the “generate and test” problem solving approach. The program generated notes pseudo-randomly by means of Markov c ...
... Hiller and Isaacson (1958) work, on the ILLIAC computer, is the best known pioneering work in computer music. Their chief result is the Illiac Suite, a string quartet composed following the “generate and test” problem solving approach. The program generated notes pseudo-randomly by means of Markov c ...
Human-Robot-Communication and Machine Learning
... will treat the learning tasks from a rather objectivistic point of view, assuming that the reference for the meaning of symbols used for communication will be the user's understanding of these symbols. The robot does not { at least for communication purposes { construct its own symbols, but grounds ...
... will treat the learning tasks from a rather objectivistic point of view, assuming that the reference for the meaning of symbols used for communication will be the user's understanding of these symbols. The robot does not { at least for communication purposes { construct its own symbols, but grounds ...
ShimonWhiteson - Homepages of UvA/FNWI staff
... our ability to solve complex, real-world problems. Consequently, my research focuses on the key algorithmic challenges that arise in developing control systems for such agents. These systems enable agents to make decisions and adapt to their environments so as to efficiently achieve their goals. In ...
... our ability to solve complex, real-world problems. Consequently, my research focuses on the key algorithmic challenges that arise in developing control systems for such agents. These systems enable agents to make decisions and adapt to their environments so as to efficiently achieve their goals. In ...
ppt - STI Innsbruck
... – If all positive examples are already true in the minimal model of the background knowledge, then no hypothesis we derive will add useful information Posterior Sufficiency: all e in E+ are true in M+(B ∪ H) – All positive examples are true (explained by the hypothesis) in the minimal model of the b ...
... – If all positive examples are already true in the minimal model of the background knowledge, then no hypothesis we derive will add useful information Posterior Sufficiency: all e in E+ are true in M+(B ∪ H) – All positive examples are true (explained by the hypothesis) in the minimal model of the b ...
11_Artificial_Intelligence-InductiveLogicProgramming
... – If all positive examples are already true in the minimal model of the background knowledge, then no hypothesis we derive will add useful information Posterior Sufficiency: all e in E+ are true in M+(B ∪ H) – All positive examples are true (explained by the hypothesis) in the minimal model of the b ...
... – If all positive examples are already true in the minimal model of the background knowledge, then no hypothesis we derive will add useful information Posterior Sufficiency: all e in E+ are true in M+(B ∪ H) – All positive examples are true (explained by the hypothesis) in the minimal model of the b ...
Tech_Trends_Knowledge Based_Crowe_FINAL
... artificial intelligence. John McCarthy was credited with devising the term artificial intelligence in 1956, and the philosophical conflict between these two concepts has continued for more than half a century (Lavenda, 2016). Augmented intelligence refers to increasing the capability of human beings ...
... artificial intelligence. John McCarthy was credited with devising the term artificial intelligence in 1956, and the philosophical conflict between these two concepts has continued for more than half a century (Lavenda, 2016). Augmented intelligence refers to increasing the capability of human beings ...