Despite significant progress in natural language understanding, Large Language Models (LLMs) remain error-prone when performing logical reasoning, often lacking the robust mental representations that enable human-like comprehension. We introduce a prototype neurosymbolic system, Embodied-LM, that grounds understanding and logical reasoning in schematic representations based on image schemas-recurring patterns derived from sensorimotor experience that structure human cognition. Our system operationalizes the spatial foundations of these cognitive structures using declarative spatial reasoning within Answer Set Programming. Through evaluation on logical deduction problems, we demonstrate that LLMs can be guided to interpret scenarios through embodied cognitive structures, that these structures can be formalized as executable programs, and that the resulting representations support effective logical reasoning with enhanced interpretability. While our current implementation focuses on spatial primitives, it establishes the computational foundation for incorporating more complex and dynamic representations.

Over the break between semesters, I've spent a lot of time with family playing a popular board game called Codenames. If you haven't played, the gist is that one player from each team, the'spymaster', tries to get their team members to select their team's assigned words from a group of 25 while avoiding the other team's words and a game-ending'assassin' word, using one word clues. It's like the game show Password, except clues can apply to any number of words. It's a fun language based game and makes for an interesting testbed for simple experiments like the one I'm about to talk about. Naturally, I thought about how a computer might play this game.

This problem is particularly pronounced for operations planners and controllers, who must be very highly knowledgeable and experienced with the business domain. This article is a case study of how one of the largest travel agencies in Hong Kong alleviated this problem by using AI to support decision making and problem solving so that its planners and controllers can work more effectively and efficiently to sustain business growth while maintaining consistent quality of service. AI is used in a mission-critical fleet management system (FMS) that supports the scheduling and management of a fleet of luxury limousines for business travelers. The AI problem was modeled as a constraint-satisfaction problem (CSP). The use of AI enabled the travel agency to sign up additional hotel partners, handle more orders, and expand its fleet with its existing team of planners and controllers.

Ride-hailing service Uber has sounded out car companies about placing a large order for self-driving cars, an auto industry source has said. "They wanted autonomous cars," the source, who declined to be named, said. "It seemed like they were shopping around." Loss-making Uber would make drastic savings on its biggest cost -- drivers -- if it were able to incorporate self-driving cars into its fleet. Volkswagen's Audi, Daimler's Mercedes-Benz, BMW and car industry suppliers Bosch and Continental are all working on technologies for autonomous or semi-autonomous cars.

Shedding drivers would save Uber a lot of money. Ride-hailing service Uber has sounded out car companies about placing a large order for self-driving cars, an auto industry source has said. "They wanted autonomous cars," the source, who declined to be named, said. "It seemed like they were shopping around." Loss-making Uber would make drastic savings on its biggest cost -- drivers -- if it were able to incorporate self-driving cars into its fleet.

Ride-hailing service Uber has sounded out car companies about placing a large order for self-driving cars and may have placed a giant order with Mercedes for 100,000 limousines, it has been claimed. 'They wanted autonomous cars,' a source, who declined to be named, told Reuters. Uber has sounded out car companies about placing a large order for self-driving cars and may have placed a giant order with Mercedes for 100,000 S-Class limousines, it has been claimed. Uber is already testing an early version of its system, which is being developed with Carnegie Mellon University. The firm hopes to develop a self driving taxi to take on autonomous car projects from Google, Apple and others. Loss-making Uber would make drastic savings on its biggest cost -- drivers -- if it were able to incorporate self-driving cars into its fleet.