Zobrazeno 1 - 10
of 89
pro vyhledávání: '"Prashant Doshi"'
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-19 (2022)
Abstract Decision making under uncertainty in multiagent settings is of increasing interest in decision science. The degree to which human agents depart from computationally optimal solutions in socially interactive settings is generally unknown. Suc
Externí odkaz:
https://doaj.org/article/584621444fc44f84b0bf19118d820292
A multiagent sequential decision problem has been seen in many critical applications including urban transportation, autonomous driving cars, military operations, etc. Its widely known solution, namely multiagent reinforcement learning, has evolved t
Externí odkaz:
http://arxiv.org/abs/2410.20954
Autor:
Priti P Parikh, Todd A Minning, Vinh Nguyen, Sarasi Lalithsena, Amir H Asiaee, Satya S Sahoo, Prashant Doshi, Rick Tarleton, Amit P Sheth
Publikováno v:
PLoS Neglected Tropical Diseases, Vol 6, Iss 1, p e1458 (2012)
BackgroundResearch on the biology of parasites requires a sophisticated and integrated computational platform to query and analyze large volumes of data, representing both unpublished (internal) and public (external) data sources. Effective analysis
Externí odkaz:
https://doaj.org/article/edbacf58232f44f398c51787722e6cb0
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 35:15224-15231
We present a novel AI-based methodology that identifies phases of a host-level cyber attack simply from system call logs. System calls emanating from cyber attacks on hosts such as honey pots are often recorded in audit logs. Our methodology first in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b458d9ca4ece3c9c018e90d22b158cb2
https://doi.org/10.1609/aaai.v35i17.17786
https://doi.org/10.1609/aaai.v35i17.17786
Publikováno v:
Proceedings of the International Conference on Automated Planning and Scheduling. 31:606-614
Sum-product networks (SPN) are knowledge compilation models and are related to other graphical models for efficient probabilistic inference such as arithmetic circuits and AND/OR graphs. Recent investigations into generalizing SPNs have yielded sum-p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41bc9257d611efc4faa1747cfd800f9e
https://doi.org/10.1609/icaps.v31i1.16009
https://doi.org/10.1609/icaps.v31i1.16009
Publikováno v:
Neurocomputing. 420:36-56
A partially observable stochastic game (POSG) is a general model for multiagent decision making under uncertainty. Perkins’ Monte Carlo exploring starts for partially observable Markov decision process (POMDP) (MCES-P) integrates Monte Carlo explor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::996cc8f47609ff87d894c831dedd4099
https://doi.org/10.1016/j.neucom.2020.08.054
https://doi.org/10.1016/j.neucom.2020.08.054
Publikováno v:
IJCAI
The sum-product network (SPN) has been extended to model sequence data with the recurrent SPN (RSPN), and to decision-making problems with sum-product-max networks (SPMN). In this paper, we build on the concepts introduced by these extensions and pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ced2d291aa44158b14303c91adc8f13
https://doi.org/10.24963/ijcai.2021/348
https://doi.org/10.24963/ijcai.2021/348
Publikováno v:
AAAI
The problem of learning an expert’s unknown reward function using a limited number of demonstrations recorded from the expert’s behavior is investigated in the area of inverse reinforcement learning (IRL). To gain traction in this challenging and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5538677625da69cf1ab0578539fa7b1e
https://doi.org/10.1609/aaai.v33i01.33013951
https://doi.org/10.1609/aaai.v33i01.33013951
Publikováno v:
IEEE Transactions on Intelligent Vehicles. 4:287-297
Merging in congested freeway traffic is a significant challenge toward realizing fully automated (level 4) driving. Merging vehicles need to decide not only how to merge safely into a spot, but also where to merge. We present a method for freeway mer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e65430f5a9f7a7ec2ce91eb936261b7
https://doi.org/10.1109/tiv.2019.2904417
https://doi.org/10.1109/tiv.2019.2904417
Publikováno v:
ICRA
Multi-task IRL recognizes that expert(s) could be switching between multiple ways of solving the same problem, or interleaving demonstrations of multiple tasks. The learner aims to learn the reward functions that individually guide these distinct way
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a70e02dd0cfb84bdb55458cb4fb3f07f
https://doi.org/10.1109/icra48506.2021.9561771
https://doi.org/10.1109/icra48506.2021.9561771