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Synthesizing efficient systems in probabilistic environments

Christian von Essen, Barbara Jobstmann, David Parker, Rahul Varshneya
2015 Acta Informatica  
In this paper we show how to automatically synthesize a system that has an "efficient" average-case behaviour in a given environment.  ...  We now can ask for an efficient system in a probabilistic environment. We model the system and the monitor as transducers and the environment as an MDP.  ... 
doi:10.1007/s00236-015-0237-y fatcat:rtkifoucajhevhtj62d2afo46a

Gist: A Solver for Probabilistic Games [chapter]

Krishnendu Chatterjee, Thomas A. Henzinger, Barbara Jobstmann, Arjun Radhakrishna
2010 Lecture Notes in Computer Science  
Our tool provides the first and efficient implementations of several reduction-based techniques to solve turn-based probabilistic games, and uses the analysis of turn-based probabilistic games for synthesizing  ...  Gist is a tool that (a) solves the qualitative analysis problem of turn-based probabilistic games with ω-regular objectives; and (b) synthesizes reasonable environment assumptions for synthesis of unrealizable  ...  The synthesized system is obtained from a witness strategy of the parity game. The flow is illustrated in Figure 1 . We illustrate, how our tool works, on a simple example.  ... 
doi:10.1007/978-3-642-14295-6_57 fatcat:fgor2uhdlrcw7ngv2utv7lqtmu

TEMPEST – Synthesis Tool for Reactive Systems and Shields in Probabilistic Environments [article]

Stefan Pranger, Bettina Könighofer, Lukas Posch, Roderick Bloem
2021 arXiv   pre-print
We present Tempest, a synthesis tool to automatically create correct-by-construction reactive systems and shields from qualitative or quantitative specifications in probabilistic environments.  ...  Furthermore, Tempest adds the functionality to synthesize safe and optimal strategies that implement reactive systems and shields  ...  In future work, we will investigate in efficient techniques to deal with partial information.  ... 
arXiv:2105.12588v1 fatcat:4av5nffijbem7b2zdrhrubixmu

Efficient synthesis of probabilistic programs

Aditya V. Nori, Sherjil Ozair, Sriram K. Rajamani, Deepak Vijaykeerthy
2015 Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation - PLDI 2015  
Our algorithm efficiently synthesizes a probabilistic program that is most consistent with the data.  ...  A core difficulty in synthesizing probabilistic programs is computing the likelihood L(P | D) of a candidate program P generating data D.  ...  Even though sketches prune the search space, efficiently synthesizing probabilistic programs is still computationally challenging due to reasons we describe next.  ... 
doi:10.1145/2737924.2737982 dblp:conf/pldi/NoriORV15 fatcat:6k3nkkbzfra5vplekzxot3rsoi

Efficient synthesis of probabilistic programs

Aditya V. Nori, Sherjil Ozair, Sriram K. Rajamani, Deepak Vijaykeerthy
2015 SIGPLAN notices  
Our algorithm efficiently synthesizes a probabilistic program that is most consistent with the data.  ...  A core difficulty in synthesizing probabilistic programs is computing the likelihood L(P | D) of a candidate program P generating data D.  ...  Even though sketches prune the search space, efficiently synthesizing probabilistic programs is still computationally challenging due to reasons we describe next.  ... 
doi:10.1145/2813885.2737982 fatcat:4zrdv2tnhvb67dowwxnpflj6ii

Safe Autonomy Under Perception Uncertainty Using Chance-Constrained Temporal Logic

Susmit Jha, Vasumathi Raman, Dorsa Sadigh, Sanjit A. Seshia
2017 Journal of automated reasoning  
These systems often operate in uncertain environments and in the presence of noisy sensors, and use machine learning and statistical sensor fusion algorithms to form an internal model of the world that  ...  is inherently probabilistic.  ...  The difficulty of this task is further amplified by the uncertain environment in which these systems operate, and the inherent probabilistic nature of the statistical techniques used to observe the environment  ... 
doi:10.1007/s10817-017-9413-9 fatcat:wfb2bqprcbhd5k6iapjb3yiddm

GIST: A Solver for Probabilistic Games [article]

Krishnendu Chatterjee, Thomas A. Henzinger, Barbara Jobstmann, Arjun Radhakrishna
2010 arXiv   pre-print
Our tool provides the first and efficient implementations of several reduction-based techniques to solve turn-based probabilistic games, and uses the analysis of turn-based probabilistic games for synthesizing  ...  Gist is a tool that (a) solves the qualitative analysis problem of turn-based probabilistic games with ω-regular objectives; and (b) synthesizes reasonable environment assumptions for synthesis of unrealizable  ...  The synthesized system is obtained from a witness strategy of the parity game. The flow is illustrated in Figure 1 .  ... 
arXiv:1004.2367v1 fatcat:2typwnm52fairfz7v2qmn5zhgq

Safe Control under Uncertainty [article]

Dorsa Sadigh, Ashish Kapoor
2015 arXiv   pre-print
We demonstrate our approach by synthesizing safe controllers under the PrSTL specifications for multiple case studies including control of quadrotors and autonomous vehicles in dynamic environments.  ...  In this paper, we propose a new logic, Probabilistic Signal Temporal Logic (PrSTL), as an expressive language to define the stochastic properties, and enforce probabilistic guarantees on them.  ...  It is appealing to consider such predictive systems in synthesizing safe controllers for dynamical systems.  ... 
arXiv:1510.07313v1 fatcat:txjltj7qnjbl5f4473h725s6za

Automatic Synthesis of Experiment Designs from Probabilistic Environment Specifications [article]

Craig Innes, Yordan Hristov, Georgios Kamaras, Subramanian Ramamoorthy
2021 arXiv   pre-print
This paper presents an extension to the probabilistic programming language ProbRobScene, allowing users to automatically synthesize uniform experiment designs directly from environment specifications.  ...  We demonstrate its effectiveness on a number of environment specification snippets from tabletop manipulation, and show that our method generates reliably low-discrepancy designs.  ...  Autonomous Systems Governance and Regulation (EP/V026607/1).  ... 
arXiv:2107.00093v1 fatcat:hyqvuuodvvhubj4kscrf4rlwq4

A Scientific Approach To Practical Induction [chapter]

Larry Rendell
1986 The Kluwer International Series in Engineering and Computer Science  
environments and inductive power of systems [18, 19, 20, 21] .  ...  In conrronting this question, some researchers have synthesized systems and created .F models, although this work is just beginning [2, 3, 5, 9, 19] .  ... 
doi:10.1007/978-1-4613-2279-5_55 fatcat:ubward26nneopo5o6tsxuw4e3m

Towards Verified Artificial Intelligence [article]

Sanjit A. Seshia, Dorsa Sadigh, S. Shankar Sastry
2020 arXiv   pre-print
Verified artificial intelligence (AI) is the goal of designing AI-based systems that that have strong, ideally provable, assurances of correctness with respect to mathematically-specified requirements.  ...  Acknowledgments The authors' work has been supported in part by NSF grants CCF-1139138, CCF-1116993, CNS-1545126 (VeHICaL), CNS-1646208, and CCF-1837132 (FMitF), by an NDSEG Fellowship, by the TerraSwarm  ...  We expect that in many cases, such probabilistic programs will need to be learned/synthesized (in part) from data.  ... 
arXiv:1606.08514v4 fatcat:ozoldsdnzjghddhwz5xju6zqvu

Toward verified artificial intelligence

Sanjit A. Seshia, Dorsa Sadigh, S. Shankar Sastry
2022 Communications of the ACM  
Making AI more trustworthy with a formal methods-based approach to AI system verification and validation.  ...  Acknowledgments Our work has been supported in part by the National Science Foundation (NSF), the Defense Advanced Research Projects Agency (DARPA), the Semiconductor Research Corporation (SRC), and several  ...  We expect that in many cases, such probabilistic programs will need to be learned/synthesized (in part) from data.  ... 
doi:10.1145/3503914 fatcat:ggc543oemfah3mboiftldvotuq

Quantum computation

L.K. Grover
1999 Proceedings Twelfth International Conference on VLSI Design. (Cat. No.PR00013)  
In order to describe the behavior of a classical probabilistic system, we need to specify probabilities of each state.  ...  This results in interference of different possibilities as in wave mechanics; this is what distinguishes quantum mechanical systems from classical probabilistic systems.  ... 
doi:10.1109/icvd.1999.745212 dblp:conf/vlsid/Grover99 fatcat:cvtya5pd3vd4lapgyjgkzcygpy

RaPiD: a toolkit for reliability analysis of non-deterministic systems

Lin Gui, Jun Sun, Yang Liu, Truong Khanh Nguyen, Jin Song Dong
2014 Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2014  
First, to have reliability assurance on a system, RaPiD can synthesize the overall system reliability given the reliability values of system components.  ...  In this work, we present a toolkit RaPiD for the reliability analysis of non-deterministic systems.  ...  Efficiency We improve the efficiency of reachability checking, which is fundamental in our reliability analysis.  ... 
doi:10.1145/2635868.2661668 dblp:conf/sigsoft/Gui00ND14 fatcat:pzlfg4e2d5hrjgar6os7ifnqxm

Deceptive Decision-Making under Uncertainty

Yagiz Savas, Christos K. Verginis, Ufuk Topcu
2022 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
We study the design of autonomous agents that are capable of deceiving outside observers about their intentions while carrying out tasks in stochastic, complex environments.  ...  The proposed approach enables the agent to exhibit a variety of tunable deceptive behaviors while ensuring the satisfaction of probabilistic constraints on the behavior.  ...  Acknowledgements This work is supported in part by the grants ARL W911NF-17-2-0181, ARL ACC-APG-RTP W911NF1920333, and AFRL FA9550-19-1-0169.  ... 
doi:10.1609/aaai.v36i5.20470 fatcat:qgxvfvw7rjhttcoliczftwlsx4
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