Collaboration requires agents to coordinate their behavior on the fly, sometimes cooperating to solve a single task together and other times dividing it up into sub‐tasks to work on in parallel. Underlying the human ability to collaborate is theory‐of‐mind (ToM), the ability to infer the hidden mental states that drive others to act. Here, we develop Bayesian Delegation, a decentralized multi‐agent learning mechanism with these abilities. Bayesian Delegation enables agents to rapidly infer the hidden intentions of others by inverse planning. (...) We test Bayesian Delegation in a suite of multi‐agent Markov decision processes inspired by cooking problems. On these tasks, agents with Bayesian Delegation coordinate both their high‐level plans (e.g., what sub‐task they should work on) and their low‐level actions (e.g., avoiding getting in each other's way). When matched with partners that act using the same algorithm, Bayesian Delegation outperforms alternatives. Bayesian Delegation is also a capable ad hoc collaborator and successfully coordinates with other agent types even in the absence of prior experience. Finally, in a behavioral experiment, we show that Bayesian Delegation makes inferences similar to human observers about the intent of others. Together, these results argue for the centrality of ToM for successful decentralized multi‐agent collaboration. (shrink)

In this work, the significance of combining the evidence from multitaper mel-frequency cepstral coefficients, linear prediction residual, and linear prediction residual phase features for multilingual speaker identification with the constraint of limited data condition is demonstrated. The LPR is derived from linear prediction analysis, and LPRP is obtained by dividing the LPR using its Hilbert envelope. The sine-weighted cepstrum estimators with six tapers are considered for multitaper MFCC feature extraction. The Gaussian mixture model–universal background model is used for modeling each (...) speaker for different evidence. The evidence is then combined at scoring level to improve the performance. The monolingual, crosslingual, and multilingual speaker identification studies were conducted using 30 randomly selected speakers from the IITG multivariability speaker recognition database. The experimental results show that the combined evidence improves the performance by nearly 8–10% compared with individual evidence. (shrink)

Science is strengthened not by research alone, but by publication of original research articles in international scientific journals that gets read by a global scientific community. Research publication is the 'heart' of a journal and the 'soul' of science - the outcome of collective efforts of authors, editors and reviewers. The publication process involves author-editor interaction for which both of them get credit once the article gets published - the author directly, the editor indirectly. However, the remote reviewer who also (...) plays a key role in the process remains anonymous and largely unrecognised. Many potential reviewers therefore, stay away from this 'highly honorary' task. Appropriate peer review controls quality of an article and thereby ensures quality and integrity of the journal. Recognising and rewarding the role of the reviewer is therefore vital. In this article, we propose a novel idea of Reviewer Index (RI), Reviewer Index Directory (RID) and Global Reviewer Index Directory (GRID), which will strengthen science by focussing on the reviewer, as well as the author. By adopting this innovative Reviewer Centric Approach, a new breed of well-trained reviewers of high quality and sufficient quantity will be available for eternity. Moreover, RI, RID and GRID would also enable grading and ethical rewarding of reviewers. (shrink)