Neuro-controller with dynamic learning and adaptation

1993 ◽  
Vol 7 (2) ◽  
pp. 151-173 ◽  
Author(s):  
M. M. Gupta ◽  
D. H. Rao ◽  
P. N. Nikiforuk
Keyword(s):  
Dynamic Learning ◽  
Learning And Adaptation ◽  
Neuro Controller

Architecture for an Artificial Immune System

2000 ◽  
Vol 8 (4) ◽  
pp. 443-473 ◽  
Author(s):  
Steven A. Hofmeyr ◽  
Stephanie Forrest
Keyword(s):  
Immune System ◽  
Computer Security ◽  
Artificial Immune System ◽  
Detection System ◽  
Classifier Systems ◽  
Artificial Immune ◽  
Dynamic Learning ◽  
Self Monitoring ◽  
Network Intrusion ◽  
Learning And Adaptation

An artificial immune system (ARTIS) is described which incorporates many properties of natural immune systems, including diversity, distributed computation, error tolerance, dynamic learning and adaptation, and self-monitoring. ARTIS is a general framework for a distributed adaptive system and could, in principle, be applied to many domains. In this paper, ARTIS is applied to computer security in the form of a network intrusion detection system called LISYS. LISYS is described and shown to be effective at detecting intrusions, while maintaining low false positive rates. Finally, similarities and differences between ARTIS and Holland's classifier systems are discussed.

Dynamic Learning Groups

ASHA Leader ◽  
2009 ◽  
Vol 14 (5) ◽  
pp. 2-2
Author(s):  
Larry Boles ◽  
Amy J. Hadley ◽  
Jeanne M. Johnson ◽  
Joan A. Luckhurst ◽  
Christine Krkovich
Keyword(s):  
Dynamic Learning ◽  
Learning Groups

Constructing and Evaluating a Validation Argument for a Next-Generation Alternate Assessment

2020 ◽  
Author(s):  
Amy K. Clark ◽  
Meagan Karvonen
Keyword(s):  
Data Collection ◽  
Assessment System ◽  
Alternate Assessment ◽  
Theory Of Action ◽  
Validity Evidence ◽  
Dynamic Learning ◽  
Alternate Assessments ◽  
Overall Evaluation ◽  
Computer Based ◽  
Achievement Standards

Alternate assessments based on alternate achievement standards (AA-AAS) have historically lacked broad validity evidence and an overall evaluation of the extent to which evidence supports intended uses of results. An expanding body of validation literature, the funding of two AA-AAS consortia, and advances in computer-based assessment have supported improvements in AA-AAS validation. This paper describes the validation approach used with the Dynamic Learning Maps® alternate assessment system, including development of the theory of action, claims, and interpretive argument; examples of evidence collected; and evaluation of the evidence in light of the maturity of the assessment system. We focus especially on claims and sources of evidence unique to AA-AAS and especially the Dynamic Learning Maps system design. We synthesize the evidence to evaluate the degree to which it supports the intended uses of assessment results for the targeted population. Considerations are presented for subsequent data collection efforts.

scholarly journals Processing of novel food reveals payoff and rank-biased social learning in a wild primate

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Charlotte Canteloup ◽  
Mabia B. Cera ◽  
Brendan J. Barrett ◽  
Erica van de Waal
Keyword(s):  
Social Learning ◽  
Learning Strategies ◽  
Individual Learning ◽  
Diffusion Experiment ◽  
Vervet Monkeys ◽  
Dynamic Learning ◽  
Novel Food ◽  
Bias Attention ◽  
Higher Rank ◽  
Learning From Others

AbstractSocial learning—learning from others—is the basis for behavioural traditions. Different social learning strategies (SLS), where individuals biasedly learn behaviours based on their content or who demonstrates them, may increase an individual’s fitness and generate behavioural traditions. While SLS have been mostly studied in isolation, their interaction and the interplay between individual and social learning is less understood. We performed a field-based open diffusion experiment in a wild primate. We provided two groups of vervet monkeys with a novel food, unshelled peanuts, and documented how three different peanut opening techniques spread within the groups. We analysed data using hierarchical Bayesian dynamic learning models that explore the integration of multiple SLS with individual learning. We (1) report evidence of social learning compared to strictly individual learning, (2) show that vervets preferentially socially learn the technique that yields the highest observed payoff and (3) also bias attention toward individuals of higher rank. This shows that behavioural preferences can arise when individuals integrate social information about the efficiency of a behaviour alongside cues related to the rank of a demonstrator. When these preferences converge to the same behaviour in a group, they may result in stable behavioural traditions.

Effects of learning and adaptation on population viability

2021 ◽  
Author(s):  
Naomi L. Indigo ◽  
Chris J. Jolly ◽  
Ella Kelly ◽  
James Smith ◽  
Jonathan K. Webb ◽  
...  
Keyword(s):  
Population Viability ◽  
Learning And Adaptation
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