A variety of theoretically-sound policy gradient algorithms exist for the on-policy setting due to the policy gradient theorem, which provides a simplified form for the gradient. The off-policy setting, however, has been less clear due to the existence of multiple objectives and the lack of an explicit off-policy policy gradient theorem. In this work, we unify these objectives into one off-policy objective, and provide a policy gradient theorem for this unified objective. The derivation involves emphatic weightings and interest functions. We show multiple strategies to approximate the gradients, in an algorithm called Actor Critic with Emphatic weightings (ACE). We prove in a counterexample that previous (semi-gradient) off-policy actor-critic methods--particularly Off-Policy Actor-Critic (OffPAC) and Deterministic Policy Gradient (DPG)--converge to the wrong solution whereas ACE finds the optimal solution. We also highlight why these semi-gradient approaches can still perform well in practice, suggesting strategies for variance reduction in ACE. We empirically study several variants of ACE on two classic control environments and an image-based environment designed to illustrate the tradeoffs made by each gradient approximation. We find that by approximating the emphatic weightings directly, ACE performs as well as or better than OffPAC in all settings tested.

According to experts, the first thing that should be kept in mind is that AI should only assist humans in efficient decision making instead of making decisions on its own. By Tejaswini Singhal Things were simpler in the Black and White era of the Human Resource procedures and recruitment than they are today. The reason for this is that the demands, challenges, and options available to HR managers back then were very different from those available today. The world of recruitment has changed as artificial intelligence (AI) is quickly becoming a must-have tool in every recruiter's toolbox. Skillsets have changed and are constantly changing.

We construct a new distribution for the simplex using the Kumaraswamy distribution and an ordered stick-breaking process. We explore and develop the theoretical properties of this new distribution and prove that it exhibits symmetry under the same conditions as the well-known Dirichlet. Like the Dirichlet, the new distribution is adept at capturing sparsity but, unlike the Dirichlet, has an exact and closed form reparameterization--making it well suited for deep variational Bayesian modeling. We demonstrate the distribution's utility in a variety of semi-supervised auto-encoding tasks. In all cases, the resulting models achieve competitive performance commensurate with their simplicity, use of explicit probability models, and abstinence from adversarial training.

As political parties gear up for the 2019 general elections, Analytics India Magazine walks down the memory lane and takes stock of the times when leaders were quite gracious in praising and educating the mass about the importance of emerging technologies like artificial intelligence and machine learning. After his tumultuous election win, the Janata Dal (Secular) supremo, HD Kumaraswamy has stepped into the shoes of his predecessor with ease in Karnataka. In fact, Kumaraswamy has been quite vocal about the role of AI in shaping the future of the state's economy. On turning the state capital into a global innovation hub: With the government playing a crucial role in bringing various stakeholders from across the country under one roof, state-sponsored Bengaluru Tech Summit has played a vital role in ushering innovation and impact. While addressing a press meet the CM said, "Bengaluru has emerged as one of the global innovation hubs in the league of Tokyo in Japan, Silicon Valley in the US and Tel Aviv in Israel. The summit will provide a platform for knowledge sharing on emerging technologies like Artificial Intelligence, Robotics and Blockchain," Kumaraswamy said.

The theme is'Innovation and Impact', and the event will include multi-track conference, business-to-business expo, thought leaders conclave as well as opportunity for startups to showcase their innovations. The conference will have over 250 experts addressing more than 3,500 delegates. Chief Minister H.D. Kumaraswamy said Bengaluru has emerged as one of the top global innovation hubs in the league of Tokyo, Silicon Valley and Tel Aviv. "Bengaluru Tech Summit will provide a platform for knowledge-sharing on emerging technologies such as Blockchain, AI (Artificial Intelligence) and robotics," said Mr. Kumaraswamy in a statement. "The event will provide an excellent opportunity to both industry and stakeholders to connect with the best minds to explore how to fuel their business growth," said K.J. George, Minister for Large and Medium Scale Industries, IT, BT and Science and Technology, Government of Karnataka, in a statement.