--Typically, research on Explainable Artificial Intelligence (XAI) focuses on black-box models within the context of a general policy in a known, specific domain. This paper advocates for the need for knowledge-agnostic explainability applied to the subfield of XAI called Explainable Search, which focuses on explaining the choices made by intelligent search techniques. It proposes Monte-Carlo Tree Search (MCTS) enhancements as a solution to obtaining additional data and providing higher-quality explanations while remaining knowledge-free, and analyzes the most popular enhancements in terms of the specific types of explainability they introduce. So far, no other research has considered the explainability of MCTS enhancements. We present a proof-of-concept that demonstrates the advantages of utilizing enhancements.

This study investigates the potential of hybrid metaheuristic algorithms to enhance the training of Probabilistic Neural Networks (PNNs) by leveraging the complementary strengths of multiple optimisation strategies. Traditional learning methods, such as gradient-based approaches, often struggle to optimise high-dimensional and uncertain environments, while single-method metaheuristics may fail to exploit the solution space fully. To address these challenges, we propose the constrained Hybrid Metaheuristic (cHM) algorithm, a novel approach that combines multiple population-based optimisation techniques into a unified framework. The proposed procedure operates in two phases: an initial probing phase evaluates multiple metaheuristics to identify the best-performing one based on the error rate, followed by a fitting phase where the selected metaheuristic refines the PNN to achieve optimal smoothing parameters. This iterative process ensures efficient exploration and convergence, enhancing the network's generalisation and classification accuracy. cHM integrates several popular metaheuristics, such as BAT, Simulated Annealing, Flower Pollination Algorithm, Bacterial Foraging Optimization, and Particle Swarm Optimisation as internal optimisers. To evaluate cHM performance, experiments were conducted on 16 datasets with varying characteristics, including binary and multiclass classification tasks, balanced and imbalanced class distributions, and diverse feature dimensions. The results demonstrate that cHM effectively combines the strengths of individual metaheuristics, leading to faster convergence and more robust learning. By optimising the smoothing parameters of PNNs, the proposed method enhances classification performance across diverse datasets, proving its application flexibility and efficiency.

We develop a method of adapting the AlphaZero model to General Game Playing (GGP) that focuses on faster model generation and requires less knowledge to be extracted from the game rules. The dataset generation uses MCTS playing instead of self-play; only the value network is used, and attention layers replace the convolutional ones. This allows us to abandon any assumptions about the action space and board topology. We implement the method within the Regular Boardgames GGP system and show that we can build models outperforming the UCT baseline for most games efficiently.

Artificial intelligence-powered influencers are the new social media trend. But there could be negative effects from the perfect influencers, a humane technologist warns. If you or someone you know is having thoughts of suicide, please contact the Suicide & Crisis Lifeline at 988 or 1-800-273-TALK (8255). Jury selection begins Thursday for the alleged medical abuse case that broke a Florida family apart and inspired the Netflix documentary "Take Care of Maya." In 2016, at just 10 years old, Maya Kowalski -- the girl at the center of the Netflix documentary -- was admitted to Johns Hopkins All Children's Hospital (JHAC) in St. Petersburg, Florida, for severe pain and then promptly removed from the custody of her parents after staff accused them of "medical abuse."

Doctors believe artificial intelligence is now saving lives, after a major advancement in breast cancer screenings. AI is detecting early signs of the disease, in some cases years before doctors would find the cancer on a traditional scan. If you or someone you know is having thoughts of suicide, please contact the Suicide & Crisis Lifeline at 988 or 1-800-273-TALK (8255). A new documentary highlights the story of a 10-year-old girl who was admitted to a Florida children's hospital for severe pain and then promptly removed from the custody of her parents after staff accused them of "medical abuse." Netflix's "Take Care of Maya" follows the story of Maya Kowalski and her mother, Beata Kowalski, a registered nurse, as they navigate Maya's rare, chronic neurological condition called complex regional pain syndrome (CRPS) – a poorly understood affliction that causes severe pain throughout a person's body due to nervous system dysfunction, according to the Cleveland Clinic.

We describe nearly fifteen years of General Game Playing experimental research history in the context of reproducibility and fairness of comparisons between various GGP agents and systems designed to play games described by different formalisms. We think our survey may provide an interesting perspective of how chaotic methods were allowed when nothing better was possible. Finally, from our experience-based view, we would like to propose a few recommendations of how such specific heterogeneous branch of research should be handled appropriately in the future. The goal of this note is to point out common difficulties and problems in the experimental research in the area. We hope that our recommendations will help in avoiding them in future works and allow more fair and reproducible comparisons.

I don't have a pilot's license. None of these obstacles, however, stopped me from landing a small private jet recently at Stewart International Airport in New Windsor, New York. OK, full confession: Actually, the plane landed itself. I merely pressed a single red button on the roof of the main cabin, transforming it into an autonomous aircraft. I was aboard a $2.75-million Cirrus Aircraft Vision Jet, newly outfitted with an aptly named safety system called Safe Return, which is in the final stages of getting approval from the Federal Aviation Administration.

As lawmakers consider the impact artificial intelligence will have on America's workforce, experts across the government, industry and academia this week urged Congress to confront and prioritize issues around ethics, bias and the increasing interactions between humans and robots. "Thanks to AI some weird and wonderful things are beginning to happen: Cars are learning to drive themselves, machines can now recognize your friends' faces and when you see people walking down the street talking on their phones, you don't know if they're talking to another human, or to a machine and expecting the machine to answer," Erik Brynjolfsson, Massachusetts Institute of Technology professor and director of the MIT Initiative on the Digital Economy said at a House Committee on Science, Space and Technology hearing in Washington. "Just last week, [the smart assistant] Siri tried to join into a conversation I was having about interest rates." Brynjolfsson researches the impacts that emerging information technologies have on business strategies and productivity. When prompted by a question from committee Chairwoman Haley Stevens, D-Mich., he described how considerations around ethics and bias are becoming more and more urgent as AI rapidly advances.

Technology is changing the way we work and the jobs we do. Will artificial intelligence and robots relieve us of humdrum tasks, making our working lives easier, or will they take our jobs away altogether? As part of a new series called the Future of Work, we look at the cryonics technician - who tries to help their clients cheat death. Are you open minded about the future? Do you have a medical background and can you complete tasks under time pressure? Are you comfortable working in the presence of a dead body?

Many brands have come to the same conclusion as the fictional Tyrell Corporation in "Blade Runner": by giving their products a past and a personality, they can increase their power of influence on the consumer, writes Wahyd Vannoni. The classic sci-fi film "Blade Runner" is set in 2019 Los Angeles. But one of the 1982 movie's main characters, replicant Leon Kowalski, was created yesterday -- April 10, 2017. Replicants like Kowalski were created by the fictional Tyrell Corporation, who imbued these machines with memories and a sense of personal history to better control them. Now that we've reached Kowalski's "inception day," many brands have come to the same conclusion: by giving their products a past and a personality, they can increase their power of influence on the consumer.