Human-Level AI's Killer Application: Interactive Computer Games
By John Edwin Laird, Michael van Lent. The AI Magazine, 2000
547 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/e2de7eb99484f5775fcbdf30513c4a59370dacdf
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Yoshua Bengio
- Sergey Levine
- Trevor Darrell
- Pieter Abbeel
- Percy Liang
- Mohit Bansal
- Yuxi Li
- Ruslan Salakhutdinov
Citations in the corpus
- Character-LLM: A Trainable Agent for Role-Playing (2023, background): “A continuous line of work is to serve as game NPCs (Laird and VanLent, 2001; Riedl, 2012) that aim to support cognitive functions in simulating games.”
- Measuring Intelligence through Games (2011, background): “More recently, several high-profile AI researchers have proposed games as good benchmarks for AI (Laird and van Lent (2001); Masum and Christensen (2003)).”
- Spoken Conversational AI in Video Games: Emotional Dialogue Management Increases User Engagement (2018, background): “Laird [8] explains the limitations of modern video games’ interfaces, and the role of Natural Language in this context.”
- Generative Agents: Interactive Simulacra of Human Behavior (2023, background): “To enable generative agents, we describe an architecture that extends a large language model to store a complete record of the agent’s experiences using natural language, synthesize those memories over time into higher-level reflections, and retrieve them dynamically to plan behavior.”
- Applying reinforcement learning to small scale combat in the real-time strategy game StarCraft:Broodwar (2012, methodology): “After games become increasingly photorealistic, focus now switches towards computer game AI, just as predicted by Laird and van Lent more than a decade ago [1].”
- Human-level performance in 3D multiplayer games with population-based reinforcement learning (2018, background): “Video games form an important domain for research (35).”
- High-level reinforcement learning in strategy games (2010, background): “Because creating an AI system for a video game does not require considerable hardware resources, yet may require contributions from many different research areas in order to produce a realistic system, it has been proposed as an accessible testbed for building human-level AI systems [5].”
- Adventure Games: A Challenge for Cognitive Robotics (2002, background): “As ( Laird & van Lent 2001 ) have argued, computer games provide a natural and challenging platform for artificial intelligence research.”
- An Explainable Artificial Intelligence System for Small-unit Tactical Behavior (2004, background): “While a number of researchers are working to apply research techniques to video games (Laird and van Lent 2001, Young et. al., 2004), few researchers have studied and reported on the AI techniques being developed by the video game industry.”
- Learning to play (2009, background): “However, recently computer and video games have received increased attention [5] [6] because they present challenges which are close to real world problems like that of the enormity of information in a highly selfcontained and circumscribed environment.”
- Unity: A General Platform for Intelligent Agents (2018, background): “The necessary search, decision-making and planning which make video games engaging challenges for humans are also the same challenges which interest AI researchers (Laird and VanLent, 2001).”