Robust artificial life via artificial programmed death
Reads0
Chats0
TLDR
This work introduces HADES, a self-regenerating system whose agents acknowledge their ''citizenship'' or faithfulness to the good of the system and are able to monitor their environment, and introduces protocols for system robustness via the notion of active citizenship and the fundamental property of programmed death.About:
This article is published in Artificial Intelligence.The article was published on 2008-04-01 and is currently open access. It has received 21 citations till now. The article focuses on the topics: Multi-agent system.read more
Citations
More filters
Journal ArticleDOI
Learning Navigation Behaviors End-to-End With AutoRL
TL;DR: Empirical evaluations show that AutoRL policies do not suffer from the catastrophic forgetfulness that plagues many other deep reinforcement learning algorithms, generalize to new environments and moving obstacles, are robust to sensor, actuator, and localization noise, and can serve as robust building blocks for larger navigation tasks.
Journal ArticleDOI
Integral biomathics: a post-Newtonian view into the logos of bios.
TL;DR: This paper provides a critical review of the major assumptions which guide the development of modern computer science and engineering towards emulating biological systems and explores the potential and the virtues of biology to reshape contemporary science.
Posted Content
Learning Navigation Behaviors End-to-End with AutoRL
TL;DR: In this article, point-to-point and path-following navigation behaviors are learned using an evolutionary automation layer around reinforcement learning (RL) that searches for a deep RL reward and neural network architecture with large-scale hyper-parameter optimization.
Journal ArticleDOI
Multiscale Agent-based Model of Tumor Angiogenesis
Megan Olsen,Hava T. Siegelmann +1 more
TL;DR: A three-dimensional multiscale agent-based model of tumor growth with angiogenesis, designed to easily adapt to various cancer types, is presented, although it focus on breast cancer.
Posted Content
Learning Navigation Behaviors End to End.
TL;DR: Over 500 meters of on-robot experiments show these policies generalize to new environments and moving obstacles, are robust to sensor, actuator, and localization noise, and can serve as robust building blocks for larger navigation tasks.
References
More filters
Journal ArticleDOI
Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
TL;DR: A new algorithm called Mersenne Twister (MT) is proposed for generating uniform pseudorandom numbers, which provides a super astronomical period of 2 and 623-dimensional equidistribution up to 32-bit accuracy, while using a working area of only 624 words.
Book
Theory of Self-Reproducing Automata
John von Neumann,Arthur W. Burks +1 more
TL;DR: This invention relates to prefabricated buildings and comprises a central unit having a peripheral section therearound to form a main residential part defined by an assembly of juxtaposed roofing and facing trusses.
Journal ArticleDOI
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
TL;DR: In this article, the contract net protocol has been developed to specify problem-solving communication and control for nodes in a distributed problem solver, where task distribution is affected by a negotiation process, a discussion carried on between nodes with tasks to be executed and nodes that may be able to execute those tasks.
Journal ArticleDOI
Telomere length predicts replicative capacity of human fibroblasts.
Richard C. Allsopp,Homayoun Vaziri,Christopher Patterson,S Goldstein,Edward V. Younglai,A B Futcher,Carol W. Greider,Calvin B. Harley +7 more
TL;DR: Telomere length is a biomarker of somatic cell aging in humans and is consistent with a causal role for telomere loss in this process, and fibroblasts from Hutchinson-Gilford progeria donors had short telomeres, consistent with their reduced division potential in vitro.
Book
Readings in Model-Based Diagnosis
TL;DR: This book discusses model-based diagnosis from first principles, Hierarchies, and Relaxation of Diagnostic Assumptions.