Guard patrol behavior is central to the immersion and strategic depth of stealth games, while most existing systems rely on hand-crafted routes or specialized logic that struggle to balance coverage efficiency and responsive pursuit with believable naturalness. We propose a generic, fully explainable, training-free framework that integrates global knowledge and local information via Composite Potential Fields, combining three interpretable maps-Information, Confidence, and Connectivity-into a single kernel-filtered decision criterion. Our parametric, designer-driven approach requires only a handful of decay and weight parameters-no retraining-to smoothly adapt across both occupancy-grid and NavMesh-partition abstractions. We evaluate on five representative game maps, two player-control policies, and five guard modes, confirming that our method outperforms classical baseline methods in both capture efficiency and patrol naturalness. Finally, we show how common stealth mechanics-distractions and environmental elements-integrate naturally into our framework as sub modules, enabling rapid prototyping of rich, dynamic, and responsive guard behaviors.

Artificial intelligence is growing at record-breaking speed, literally. Thanks to exponential development, AI has made its way to the Guinness book of world records. Below is a list of records in the AI domain. What started as a simple Bot Camp program became a world record for the largest artificial intelligence programming lesson. Capital One Services LLC hosted this camp as part of its Future Edge DFW initiative in Dallas, Texas, USA, on April 17 2019.

The ability to distract opponents is a key mechanic in many stealth games. Existing search-based approaches to stealth analysis, however, focus entirely on solving the non-detection problem, for which they rely on static, ahead-of-time models of guard movements that do not depend on player interaction. In this work we extend and optimize an approach based on heuristic search of stealth games to model variation in guard paths as dynamically triggered by player actions. Our design is expressive, accommodating different distraction designs, including remote activation and time delays. Using a Unity3D implementation, we show our enhanced search can solve distraction puzzles found in real games, as well as more complex, multiple-distraction level designs. Our work shows how heuristic search can be applied to dynamically determined contexts, and significantly extends the ability to model and solve stealth games.

The reference books that line the shelves of developer Ultra Ultra's modest Copenhagen office offers insight into the aesthetic of its first game, Echo. Prometheus: The Art of the Film and Star Wars provide sci-fi reference points, while Metal Gear Solid, Blame! and Neon Genesis Evangelion--all three of which are represented in some form on the shelf--provide the inspiration for character design. Echo is made up of many familiar parts, but parts that are remixed in a way that makes them feel new. This is fundamental to Echo not just aesthetically, but also mechanically. Unsurprisingly, given Ultra Ultra's staff of ex-IO Interactive Hitman developers, Echo is a stealth game.

There are tons of great-looking video games coming out in 2017. Many of these are western releases, but a huge number of fantastic titles are coming out of Japan also. In fact, many of my most hotly-anticipated games are Japanese this year. In any case, here's a list of all the best (or at least most important) video games currently announced for a 2017 release. I'll keep this list updated with other important releases as well.