Trained Behavior Trees: Programming by Demonstration to Support AI Game Designers

Learning Behavior Trees for Autonomous Agents with Hybrid Constraints Evolution

“…However, the optimal behavior may be inappropriate or unnatural. Thus, there are a few works of learning BTs from observation emerged but still an open problem [7,25]. We believe GP is a promising method and the frequent sub-tree mining can be a potential tool to facilitate behavior block building and accelerate learning.…”

“…Teng et al [22] use a self-organizing neural network to learn incrementally through real-time interactions with the environment, which can improve air combat maneuvering strategies of CGFs. Please note that most of those machine learning methods generate behavior model as a black box system [6,7]. As a result, domain expert could not produce a clear explanation of the relationship between behaviors and models, which is hard to analyze and validate.…”

“…To remedy the disadvantages, in both behavior learning perspectives, there are some attempts to generate behavior models represented as BTs from observation [7,25] or experience [11,12,14,26,27] automatically. In this paper, we are focusing on generate BTs through experiential learning, especially evolving BTs.…”

“…Through providing sample traces or evaluation criterion of experts' desired behavior, an agent can learn behavior model from expert demonstration or trial-and-error experience respectively. Nevertheless, pure ML approaches, like neuron network (NN) or reinforcement learning (RL), usually generate behavior models as black box systems, which are difficult for domain experts to understand, validate and modify [6,7].…”

Understanding everything NPCs can do

“…• Multiple smaller actions (sub-actions) can be chained together to create a behavior. Tree behaviors, such as Hierarchical Task Networks (HTNs) or Behavior Trees (BTs) are the most widely used form [5,13,18,24,29,30]. The behavior itself is a component of an action.…”