On the Crowdsourcing of Behaviors for Autonomous Agents
نویسندگان
چکیده
This letter is concerned with the problem of designing, from data, agents that are able to craft their behavior a set contributors in order fulfill some agent-specific task. not necessarily known contributors. After formalizing this crowdsourcing process as control problem, we present result synthesize behaviors information made available by The turned into an algorithm and theoretical findings complemented via example.
منابع مشابه
“the effect of risk aversion on the demand for life insurance: the case of iranian life insurance market”
abstract: about 60% of total premium of insurance industry is pertained?to life policies in the world; while the life insurance total premium in iran is less than 6% of total premium in insurance industry in 2008 (sigma, no 3/2009). among the reasons that discourage the life insurance industry is the problem of adverse selection. adverse selection theory describes a situation where the inf...
15 صفحه اولReinforcement Learning of Hierarchical Fuzzy Behaviors for Autonomous Agents
Reinforcement learning is a suitable approach to learn behaviors for Autonomous Agents, but it is usually too slow to be applied in real time on embodied agents [8]. In this paper, we present the results that we have obtained by adopting a careful design of the control architecture and of the learning sessions, aimed at reducing the learning computation. The agent learns in simplified environme...
متن کاملLearning by Imitation of Behaviors for Autonomous Agents
The goal of this work is to provide more autonomy for virtual actors by endowing them with a learning ability by imitation. While acting in his virtual world, our virtual actor uses prototypic behaviors defined by Fuzzy Cognitive Maps (FCMs) to simulate other actors’ behavior in his imaginary world. This simulation allows him to carry out predictions and choices of strategies. We propose a meth...
متن کاملLearning the suitability of simple behaviors to obtain composite behaviors for autonomous agents♣
The composition of simple behaviors is a common practice to obtain complex behaviors from autonomous agents. In this paper, we present S-ELF, a reinforcement learning approach that learns to coordinate pre-defined basic behaviors and is derived from ELF (Evolutonary Learning of Fuzzy rules) (Bonarini, 1993), (Bonarini, 1996a). S-ELF (Symbolic ELF) learns the context of activation for each of th...
متن کاملLearning to coordinate fuzzy behaviors for autonomous agents
We developed a system learning behaviors represented as sets of fuzzy rules for autonomous agents. In the past, we adopted our approach to learn successfully simple reactive behaviors, also in those cases when the evaluation function used in our reinforcement learning schema judges unevenly the different situations the autonomous agents operate on. In this paper we present a new version of our ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Control Systems Letters
سال: 2021
ISSN: ['2475-1456']
DOI: https://doi.org/10.1109/lcsys.2020.3034750