Heuristics

Online poker faces a cheating crisis. The AI revolution has imperiled the multi-billion dollar industry as computers continue to outshine humans at their own games. Poker-playing bots can now routinely thrash human experts, and it can be difficult to detect when anonymous online players are using real-time assistance engines to inform their decisions. Cheaters no longer have to brave a tableful of greedy eyes, desperate to avoid detection as they palm a card or deal from the bottom of the deck. Online poker servers have…

Setting a starting solution in MIP Models: a scheduling applicationPhoto by Nils Geldner on UnsplashIn computer science, heuristics are techniques used to find a feasible solution to a given problem, typically faster than exact methods but without a guarantee of optimality. On the other hand, exact methods are much more expensive computationally, but the optimal solution is guaranteed.Modeling a problem as a Mixed Integer Program (MIP) and solving it using a solver may give you the optimal solution. Usually, those solvers…

Searching for the best solution (on the highest top). Image by Dall-E 2.Local search, genetic algorithms, and more.There are many different ways to solve mathematical optimization problems. You can use greedy algorithms, constraint programming, mixed integer programming, genetic algorithms, local search, and others. Depending on the size and type of the problem, and the solution quality desired, one technique may work better than the other.This post gives an overview of different heuristics for solving discrete…

In this defence of heuristics, I examine how simple solutions can often be the best port of call when looking to ship data science productsPhoto by Mickey O'neil on UnsplashIn 2016, Lisa Bodell — the CEO of futurethink and a top speaker at Google events — proposed that “simplicity is fast becoming the advantage of our time”. However, within the field of data science and machine learning, we can often prefer more complex solutions, that while can typically lead to incredible results, can also lead to frustration, failures…

Heuristics in AI have huge potential but they are not always 100% right. Heuristics are shortcuts to solutions. The idea of heuristic methods in AI is based on cognitive science or the study of how humans think. Indeed, humans use heuristics all the time to make decisions and solve problems. Likewise, heuristic algorithms are often used in AI to get a computer to find an approximate solution instead of an exact solution. Heuristics don’t always lead to a lower cost. However, those that don’t overestimate the true…