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217
The adaptive nature of human categorization
- Psychological Review
, 1991
"... A rational model of human categorization behavior is presented that assumes that categorization reflects the derivation of optimal estimates of the probability of unseen features of objects. A Bayesian analysis is performed of what optimal estimations would be if categories formed a disjoint partiti ..."
Abstract
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Cited by 344 (2 self)
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of linearly nonseparable categories, effects of category labels, extraction of basic level categories, base-rate effects, probability matching in categorization, and trial-by-trial learning functions. Al-though the rational model considers just I level of categorization, it is shown how predictions can
Adversarial Classification
- IN KDD
, 2004
"... Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detection, intrusion detection, fraud detection, surveillance and counter-terrorism, this is far from the case: the data is activ ..."
Abstract
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Cited by 141 (0 self)
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is actively manipulated by an adversary seeking to make the classifier produce false negatives. In these domains, the performance of a classifier can degrade rapidly after it is deployed, as the adversary learns to defeat it. Currently the only solution to this is repeated, manual, ad hoc reconstruction
On Behavior Classification in Adversarial Environments
, 2000
"... In order for robotic systems to be successful in domains with other agents possibly interfering with the accomplishing of goals, the agents must be able to adapt to the opponents' behavior. The more quickly the agents can respond to a new situation, the better they will perform. We present an a ..."
Abstract
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Cited by 30 (1 self)
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In order for robotic systems to be successful in domains with other agents possibly interfering with the accomplishing of goals, the agents must be able to adapt to the opponents' behavior. The more quickly the agents can respond to a new situation, the better they will perform. We present
Building Adaptive Autonomous Agents for Adversarial Domains
"... This paper presents a methodology, called CAPTAIN, to build adaptive agents in an integrated framework that facilitates both building agents through knowledge elicitation and interactive apprenticeship learning from subject matter experts, and making these agents adapt and improve during their norma ..."
Abstract
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their normal use through autonomous learning. Such an automated adaptive agent consists of an adversarial planner and a muitistrategy learner. CAPTAIN agents may function as substitutes for human participants in training-oriented distributed interactive simulations. 1.
Adaptive Behavior Models for Asymmetric Adversaries
"... In order for simulation based training to help prepare warfighters for modern asymmetric tactics, opponent models of behavior must become more dynamic and challenge trainees with adaptive threats consistent with those increasingly encountered by the military. In this paper we describe an adaptive be ..."
Abstract
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Cited by 1 (1 self)
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for generalizing to other domains. The second research area is the design and development of artificial intelligence techniques for creating adaptive adversaries. The approach makes use of an authoring tool for defining adaptive behavior models specified as partial plans that can be instantiated with choices
Towards Collaborative and Adversarial Learning: A Case Study in Robotic Soccer
- INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
, 1998
"... Soccer is a rich domain for the study of multiagent learning issues. Not only must the players learn low-level skills, but they must also learn to work together and to adapt to the behaviors of different opponents. We are using a robotic soccer system to study these different types of multiagent ..."
Abstract
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Cited by 53 (11 self)
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Soccer is a rich domain for the study of multiagent learning issues. Not only must the players learn low-level skills, but they must also learn to work together and to adapt to the behaviors of different opponents. We are using a robotic soccer system to study these different types of multiagent
Towards Adversarial Reasoning in Statistical Relational Domains
"... Statistical relational artificial intelligence combines first-order logic and probability in order to handle the complexity and uncertainty present in many real-world domains. However, many real-world domains also in-clude multiple agents that cooperate or compete accord-ing to their diverse goals. ..."
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. In order to handle such do-mains, an autonomous agent must also consider the ac-tions of other agents. In this paper, we show that ex-isting statistical relational modeling and inference tech-niques can be readily adapted to certain adversarial or non-cooperative scenarios. We also discuss how learn-ing
Coupled Generative Adversarial Networks
"... Abstract We propose coupled generative adversarial network (CoGAN) for learning a joint distribution of multi-domain images. In contrast to the existing approaches, which require tuples of corresponding images in different domains in the training set, CoGAN can learn a joint distribution without an ..."
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Abstract We propose coupled generative adversarial network (CoGAN) for learning a joint distribution of multi-domain images. In contrast to the existing approaches, which require tuples of corresponding images in different domains in the training set, CoGAN can learn a joint distribution without
Heuristic Search for Coordinating Robot Agents in Adversarial Domains
, 2006
"... Abstract — This paper presents a search-based, real-time adaptive solution to the multi-robot coordination problem in adversarial environments. By decomposing the global coordination task into a set of local search problems, efficient and effective solutions to subproblems are found and combined int ..."
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Abstract — This paper presents a search-based, real-time adaptive solution to the multi-robot coordination problem in adversarial environments. By decomposing the global coordination task into a set of local search problems, efficient and effective solutions to subproblems are found and combined
Adaptive communal detection in search of adversarial identity crime
- Proceedings of the 2007 International Workshop on Domain Driven Data Mining, pp.1–10
, 2007
"... “In conflict, straightforward actions generally lead to engagement; surprising actions generally lead to victory.”- Sun Tzu, ~500 BC, “The Art of War” This paper is on adaptive real-time searching of credit application data streams for identity crime with many search parameters. Specifically, we con ..."
Abstract
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Cited by 2 (1 self)
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concentrated on handling our domain-specific adversarial activity problem with the adaptive Communal Analysis Suspicion Scoring (CASS) algorithm. CASS’s main novel theoretical contribution is in the formulation of State-of-Alert (SoA) which sets the condition of reduced, same, or heightened watchfulness
Results 1 - 10
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217
