Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Shivaram Kalyanakrishnan"'
Publikováno v:
2021 Seventh Indian Control Conference (ICC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ebb06b980221d4b05e98c218479c61b
https://doi.org/10.1109/icc54714.2021.9703176
https://doi.org/10.1109/icc54714.2021.9703176
Autor:
Shivaram Kalyanakrishnan
Publikováno v:
IJCAI
My research is driven by my curiosity about the nature of intelligence. Of the several aspects that characterise the behaviour of intelligent agents, I primarily study sequential decision making, learning, and exploration. My interests also extend to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80d6fed4a93d484c159facf1abdc5e50
https://doi.org/10.24963/ijcai.2021/700
https://doi.org/10.24963/ijcai.2021/700
Autor:
Kumar Ashutosh, Bhishma Dedhia, Shivaram Kalyanakrishnan, Parthasarathi Khirwadkar, Sarthak Consul, Sahil Shah
Publikováno v:
CDC
Policy Iteration (PI) is a classical family of algorithms to compute an optimal policy for any given Markov Decision Problem (MDP). The basic idea in PI is to begin with some initial policy and to repeatedly update the policy to one from an improving
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57df2eb61d329b7c5998a5b5c21b7f32
https://doi.org/10.1109/cdc42340.2020.9303956
https://doi.org/10.1109/cdc42340.2020.9303956
Publikováno v:
AAAI
Regret minimisation in stochastic multi-armed bandits is a well-studied problem, for which several optimal algorithms have been proposed. Such algorithms depend on (sufficient statistics of) the empirical reward distributions of the arms to decide wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41da90b38d1b3140b934018aa36b765e
Autor:
Yejin Choi, William Yeoh, Reshef Meir, Shivaram Kalyanakrishnan, Haris Aziz, Suchi Saria, Daniel Hsu, Gerardo I. Simari, Lirong Xia, Elias Bareinboim
Publikováno v:
IEEE Intelligent Systems. 31:56-66
IEEE Intelligent Systems once again selected 10 young AI scientists as " AI's 10 to Watch." This acknowledgment and celebration not only recognizes these young scientists and makes a positive impact in their academic career but also promotes the comm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::886f117803361edad59ed4140d8fff1f
https://doi.org/10.1109/mis.2016.7
https://doi.org/10.1109/mis.2016.7
Publikováno v:
AIES
In the future of India lies the future of a sixth of the world's population. As the Artificial Intelligence (AI) revolution sweeps through societies and enters daily life, its role in shaping India's development and growth is bound to be substantial.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e62b9775147db8376952d84df3029b18
https://doi.org/10.1145/3278721.3278738
https://doi.org/10.1145/3278721.3278738
Autor:
Anchit Gupta, Shivaram Kalyanakrishnan
Publikováno v:
IJCAI
The Markov Decision Problem (MDP) plays a central role in AI as an abstraction of sequential decision making. We contribute to the theoretical analysis of MDP PLANNING, which is the problem of computing an optimal policy for a given MDP. Specifically
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b935c58e6a8630931b7a5bb3248373b
https://doi.org/10.24963/ijcai.2017/248
https://doi.org/10.24963/ijcai.2017/248
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 31
We propose a PAC formulation for identifying an arm in an n-armed bandit whose mean is within a fixed tolerance of the m-th highest mean. This setup generalises a previous formulation with m = 1, and differs from yet another one which requires m such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::622de82d448793be575d99472a0d4554
https://doi.org/10.1609/aaai.v31i1.10802
https://doi.org/10.1609/aaai.v31i1.10802
Autor:
KangKang Yin, Shivaram Kalyanakrishnan, Umashankar Nagarajan, Seung-kook Yun, Ambarish Goswami, Sung-Hee Lee
Publikováno v:
Autonomous Robots. 36:199-223
Humanoid robots are expected to share human environments in the future and it is important to ensure the safety of their operation. A serious threat to safety is the fall of such robots, which can seriously damage the robot itself as well as objects
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d46e8ec9cafb9fbad68a43e05d158f8
https://doi.org/10.1007/s10514-013-9343-2
https://doi.org/10.1007/s10514-013-9343-2
Publikováno v:
IndraStra Global.
Policy Iteration (PI) (Howard 1960) is a classical method for computing an optimal policy for a finite Markov Decision Problem (MDP). The method is conceptually simple: starting from some initial policy, “policy improvement” is repeatedly perform
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f24a063ec778cb816a2a0640e6f3ff46
https://igi.indrastra.com/items/show/62208
https://igi.indrastra.com/items/show/62208