We propose a method for obtaining character behavior diversity based on the diversity of plans enacted by characters, and demonstrate this method in a scenario in which characters have multiple choices. Using case-based planning techniques, we reuse plans for varied character behavior, which simulate different personality traits.

Most likely, you're familiar with Watson from the IBM computer system's appearance on Jeopardy! in 2011, when it beat former champions Ken Jennings and Brad Rudder. Watson Health was supposed to change health care in a lot of important ways, by providing insight to oncologists about care for cancer patients, delivering insight to pharmaceutical companies about drug development, helping to match patients with clinical trials, and more. It sounded revolutionary, but it never really worked. Recently, Watson Health was, essentially, sold for parts: Francisco Partners, a private equity firm, bought some of Watson's data and analytics products for what Bloomberg News said was more than $1 billion. On Friday's episode of What Next: TBD, I spoke with Casey Ross, technology correspondent for Stat News, who has been covering Watson Health for years, about how Watson went from being the future of health care to being sold for scraps.

Ten years ago, IBM made a gamble. Through a monumental advertising and PR campaign, it promised that its AI technology–Watson–would transform the health care industry as we know it. A decade and billions of dollars later, Watson Health is being sold for parts. What went wrong with IBM's "moonshot?" And what does Watson's failure tell us about the promise of AI for health care?

A machine-learning expert and a psychology researcher/clinician may seem an unlikely duo. But MIT's Rosalind Picard and Massachusetts General Hospital's Paola Pedrelli are united by the belief that artificial intelligence may be able to help make mental health care more accessible to patients. In her 15 years as a clinician and researcher in psychology, Pedrelli says "it's been very, very clear that there are a number of barriers for patients with mental health disorders to accessing and receiving adequate care." Those barriers may include figuring out when and where to seek help, finding a nearby provider who is taking patients, and obtaining financial resources and transportation to attend appointments. Pedrelli is an assistant professor in psychology at the Harvard Medical School and the associate director of the Depression Clinical and Research Program at Massachusetts General Hospital (MGH).

IBM said Friday it will sell the core data assets of its Watson Health division to a San Francisco-based private equity firm, marking the staggering collapse of its ambitious artificial intelligence effort that failed to live up to its promises to transform everything from drug discovery to cancer care. Data and analytics assets held by the health business, which was not profitable, were sold to Francisco Partners as IBM seeks to refocus its business on cloud computing and AI services to help clients in multiple industries build machine learning tools and secure and manage their data. Terms of the transaction were not disclosed. Unlock this article by subscribing to STAT and enjoy your first 30 days free! STAT is STAT's premium subscription service for in-depth biotech, pharma, policy, and life science coverage and analysis.

Health insurance companies have been looking to artificial intelligence (AI) and machine learning to identify at-risk individuals and reduce rising costs in the healthcare sphere.

Watson, a supercomputer by IBM, shot to fame in 2011 as the'brain' that beat two of the best contestants of Jeopardy! to win a million dollars. This system that combines artificial intelligence (AI) and sophisticated analytical software to answer questions was widely deployed in many industries. The supercomputer was developed in IBM's DeepQA project and was named after IBM's founder Thomas J. Watson. "You can be discouraged by failure, or you can learn from it. So go ahead and make mistakes, make all you can. Because, remember that's where you'll find success – on the far side of failure."

Previous knowledge graph embedding approaches usually map entities to representations and utilize score functions to predict the target entities, yet they struggle to reason rare or emerging unseen entities. In this paper, we propose kNN-KGE, a new knowledge graph embedding approach, by linearly interpolating its entity distribution with k-nearest neighbors. We compute the nearest neighbors based on the distance in the entity embedding space from the knowledge store. Our approach can allow rare or emerging entities to be memorized explicitly rather than implicitly in model parameters. Experimental results demonstrate that our approach can improve inductive and transductive link prediction results and yield better performance for low-resource settings with only a few triples, which might be easier to reason via explicit memory.

Health insurance is a source of confusion, frustration and stress for many Americans. While the federal and state governments have taken measures to improve the health insurance system, many Americans still groan at the complexities and shortcomings that leave some 15% of adults ages 19-34 uninsured, and both uninsured and insured people say insurance is too expensive. Reforms to the nation's healthcare system are also insufficient for many. About 11% of uninsured people had income below the poverty level but were ineligible for Medicaid because their state did not expand the program. Even reforms to the health insurance system are not reaching most of those who still lack insurance.

Albert Pomales is Co-Founder and CEO of KindHealth, bringing complex insurance solutions to the consumer. Health insurance is a source of confusion, frustration and stress for many Americans. While the federal and state governments have taken measures to improve the health insurance system, many Americans still groan at the complexities and shortcomings that leave some 15% of adults ages 19-34 uninsured, and both uninsured and insured people say insurance is too expensive. Reforms to the nation's healthcare system are also insufficient for many. About 11% of uninsured people had income below the poverty level but were ineligible for Medicaid because their state did not expand the program.