title={Scaling-Up Behavioral Programming: Steps from Basic Principles to Application Architectures},
year={2014},
isbn={9781450321891},
publisher={Association for Computing Machinery},
address={New York, NY, USA},
url={https://doi.org/10.1145/2687357.2687359},
doi={10.1145/2687357.2687359},
abstract={Behavioral programming (BP) is a decentralized scenario-based paradigm for the programming of reactive software, geared towards incremental and intuitive development. In this work we apply the principles of BP to a large, real-world case-study: a web-server. We discuss the conclusions learned from our attempt and propose several extension idioms to BP, aimed at improving the framework's scalability. Specifically, we propose extending BP with a timeout idiom for handling various time constraints, program-specific execution strategies, dynamic thread creation for efficiently allocating system resources, and support for parameterized events to handle inputs with infinite domains. Our extensions and case-study are implemented in a new framework for behavioral programming in C++.},
booktitle={Proceedings of the 4th International Workshop on Programming Based on Actors Agents \& Decentralized Control},
pages={95–108},
numpages={14},
keywords={behavioral programming, c++, http, reactive systems, tcp, time constraints},
location={Portland, Oregon, USA},
series={AGERE! '14}
}
@inproceedings{10.1109/MODELS-C.2019.00039,
@inproceedings{10.1109/MODELS-C.2019.00039,
author={Elyasaf, Achiya and Sadon, Aviran and Weiss, Gera and Yaacov, Tom},
author={Elyasaf, Achiya and Sadon, Aviran and Weiss, Gera and Yaacov, Tom},
title={Using behavioural programming with solver, context, and deep reinforcement learning for playing a simplified RoboCup-type game},
title={Using behavioural programming with solver, context, and deep reinforcement learning for playing a simplified RoboCup-type game},
