Personalized Help for Optimizing Low-Skilled Users’ Strategy (2025)

Abstract: AIs can beat humans in game environments; however, how helpful those agents are to human remains understudied. We augment Cicero, a natural language agent that demonstrates superhuman performance in Diplomacy, to generate both move and message advice based on player intentions. A dozen Diplomacy games with novice and experienced players, with varying advice settings, show that some of the generated advice is beneficial. It helps novices compete with experienced players and in some instances even surpass them. The mere presence of advice can be advantageous, even if players do not follow it.

## related work appropriate reliance on ai: the topic of human reliance on ai is central to current research in machine learning and explainable ai. prior work measures reliance in ai-assisted decision making @xcite @xcite , and ex-plores reducing over-reliance @xcite @xcite . some researchers have examined how explanations affect human reliance on ai @xcite . however, empirical evidence from multiple domains shows conflicting results: while some show that ai explanations improve human decision making, others find evidence of over-reliance on ai explanations even when they are incorrect @xcite @xcite @xcite @xcite @xcite . for pholus, humans remain relatively conservative toward ai advice. even novice diplomacy players do not blindly follow the advice. ai as player companion: ai agents have a long history of superhuman gameplay. in 1996, ibm's deep blue defeated the reigning world chess champion, garry kasparov, although it lost several other games in the same match @xcite . more recently, deepmind's alphago @xcite consistently defeated top-rated go players, a game with exponentially complex computational space, and later changed professional go players' play style. multiagent reinforcement learning systems like alphastar @xcite and openai five @xcite also show high performance in computer games through self-play. however, these experiments focus only on game outcomes rather than how they can shape human gameplay. some studies on nlp communicative agents aim to generate guidance in a grounded @xcite . tremblay and verbrugge (2013) develop an adaptive ai companion that adjusts its behavior based on the player's experience. @xcite assess human reliance on ai-based advice by examining the skill level of ai agents and the presentation of advice. while these studies show that ais outperform non-adaptive agents in guiding players, they do not consider player intention when generating guidance. in comparison, pholus takes players' past messages and moves entered when generating personalized advice. augmented learning: this is an educational approach that enhances and personalizes the learning experience. traditionally, peer interaction simulates social interaction and helps learning @xcite . recent advancements in ai and nlp agents, suggest adaptive pedagogical interactions between humans and these agents to help learning in new environments @xcite @xcite . @xcite apply the theory of mind to generate guidance for players in dungeons and dragons. ruan et al. (2020) develop a narrative-based tutoring system and show that it helps effective learning for children. in this study, we apply the concept of augmented learning to help novices understand the game of diplomacy. ## conclusion human-ai collaboration depends on a range of factors. using the board game diplomacy, pholus provides real-time move and message advice tailored to intentions of both novice and experienced players. surprisingly, even though only some advice is accepted, it can have a substantial impact on outcomes, particularly for novice players. this is because advice can positively inform choices even if the advice isn't strictly followed. our experiments enable further study of human-ai collaboration, including modeling explicit intentions and how to better use knowledge within these models. on a broader scope, future research should consider how ai can inform people without making choices for them and measure that impact.