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Automated Decision Making for Safety Critical Applications

MBZUAI ·

Mykel Kochenderfer from Stanford University gave a talk on building robust decision-making systems for autonomous systems, highlighting the challenges of balancing safety and efficiency in uncertain environments. The talk addressed computational tractability and establishing trust in these systems. Kochenderfer outlined methodologies and research applications for building safer systems, drawing from his work on air traffic control, unmanned aircraft, and automated driving. Why it matters: The development of safe and reliable autonomous systems is crucial for various applications in the region, and insights from experts like Kochenderfer can guide research and development efforts at institutions like MBZUAI.

Rational Counterfactuals

arXiv ·

This paper introduces rational counterfactuals, a method for identifying counterfactuals that maximize the attainment of a desired consequent. The approach aims to identify the antecedent that leads to a specific outcome for rational decision-making. The theory is applied to identify variable values that contribute to peace, such as Allies, Contingency, Distance, Major Power, Capability, Democracy, and Economic Interdependency. Why it matters: The research provides a framework for analyzing and promoting conditions conducive to peace using counterfactual reasoning.

Multi-agent Time-based Decision-making for the Search and Action Problem

arXiv ·

This paper introduces a decentralized multi-agent decision-making framework for search and action problems under time constraints, treating time as a budgeted resource where actions have costs and rewards. The approach uses probabilistic reasoning to optimize decisions, maximizing reward within the given time. Evaluated in a simulated search, pick, and place scenario inspired by the Mohamed Bin Zayed International Robotics Challenge (MBZIRC), the algorithm outperformed benchmark strategies. Why it matters: The framework's validation in a Gazebo environment signals potential for real-world robotic applications, particularly in time-sensitive and cooperative tasks within the robotics domain in the UAE.

AI strategy for CEOs: Where to lead, lag, or exit - PwC

Bahrain AI ·

PwC has published a report offering strategic guidance to CEOs on navigating the landscape of artificial intelligence. The report likely outlines frameworks for determining where companies should proactively invest and innovate ('lead'), adopt standard industry practices ('lag'), or deprioritize ('exit') specific AI initiatives. It probably addresses critical aspects such as resource allocation, risk management, and competitive differentiation through AI adoption. Why it matters: This strategic counsel can assist businesses in the Middle East in formulating robust AI strategies, optimizing their investments, and enhancing their market competitiveness.

Information Design under Uncertainty

MBZUAI ·

Munther Dahleh from MIT gave a talk on information design under uncertainty, focusing on the challenges of creating an information marketplace. The talk addressed the externality faced by firms when information is allocated to competitors, and considered two models for this externality. The presentation included mechanisms for both models and highlighted the impact of competition on the revenue collected by the seller. Why it matters: The research advances understanding of information markets and mechanism design, relevant to the growing data economy in the GCC region.

Biweekly research update

KAUST ·

KAUST Discovery Professor Jesper Tegnér collaborated with UK researchers to develop algorithms explaining decision-making in insects and rats. Assoc. Prof. Robert Hoehndorf's lab introduced a tool for identifying genetic variants linked to rare diseases based on patient symptoms. KAUST scientists also studied monkeypox infection of human skin using stem cells and marine microbiome adaptation to thermal changes. Why it matters: These diverse research projects highlight KAUST's contributions to computational biology, virology, and marine science, advancing knowledge with implications for healthcare and environmental challenges.

Learn to control

MBZUAI ·

Patrick van der Smagt, Director of AI Research at Volkswagen Group, discussed the use of generative machine learning models for predicting and controlling complex stochastic systems in robotics. The talk highlighted examples in robotics and beyond and addressed the challenges of achieving quality and trust in AI systems. He also mentioned his involvement in a European industry initiative on trust in AI and his membership in the AI Council of the State of Bavaria. Why it matters: Understanding control in robotics, along with trust in AI, are key issues for further development of autonomous systems, especially in industrial applications within the GCC region.