Statements (63)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:project
|
| gptkbp:bfsLayer |
3
|
| gptkbp:bfsParent |
gptkb:stadium
|
| gptkbp:adaptation |
real-time adjustments
|
| gptkbp:agent |
strategic decision making
|
| gptkbp:audience |
mixed reviews
|
| gptkbp:collaborations |
with professional Dota 2 players
|
| gptkbp:community |
Dota 2 community
|
| gptkbp:community_impact |
inspired AI research in gaming
|
| gptkbp:contribution |
advancements in AI capabilities
|
| gptkbp:developed_by |
gptkb:Open_AI
|
| gptkbp:edibility |
human intelligence
with human players |
| gptkbp:events |
Dota 2 tournaments
|
| gptkbp:feedback |
enthusiastic
|
| gptkbp:field |
machine learning in gaming
|
| gptkbp:focus |
game strategy optimization
|
| gptkbp:future_plans |
AI in other games
|
| gptkbp:game_engine |
gptkb:Source_engine
continuous improvement through gameplay experience |
| gptkbp:game_length |
approximately 30-60 minutes
|
| gptkbp:game_replayability |
highly adaptable to strategies
|
| gptkbp:game_type |
gptkb:video_game
|
| gptkbp:gameplay |
cooperative and competitive
|
| gptkbp:goal |
compete with human players
|
| gptkbp:has_role |
carry, support, offlaner, midlaner, jungler
|
| https://www.w3.org/2000/01/rdf-schema#label |
Open AI Dota 2
|
| gptkbp:influence |
AI development strategies
|
| gptkbp:intelligence |
gptkb:Artificial_Intelligence
adaptive competitive level |
| gptkbp:is_a_supporter_of |
gptkb:2019_International_Dota_2_Championship
|
| gptkbp:map |
Dota 2 map
|
| gptkbp:match_type |
best of three
|
| gptkbp:mission |
destroy enemy towers and ancient
|
| gptkbp:notable_achievement |
defeated professional players
|
| gptkbp:notable_match |
against Evil Geniuses
against Team OG |
| gptkbp:number_of_games |
five AI players
|
| gptkbp:objective |
team-based strategy
|
| gptkbp:outcome |
new insights into AI capabilities.
|
| gptkbp:performance |
win rate
|
| gptkbp:provides_information_on |
Dota 2 gameplay data
|
| gptkbp:related_to |
gptkb:sports_event
|
| gptkbp:release_year |
gptkb:2018
|
| gptkbp:research_areas |
AI in competitive gaming
|
| gptkbp:skills |
highly skilled
high-level play |
| gptkbp:strategic_importance |
team coordination
|
| gptkbp:style_of_play |
aggressive and strategic
|
| gptkbp:tactics |
dynamic and evolving
|
| gptkbp:team |
five-player team
|
| gptkbp:technology |
reinforcement learning
|
| gptkbp:training |
several months
self-play complex decision making achieved high win rates against humans iterative training process reinforcement learning with human feedback simulated Dota 2 matches |
| gptkbp:was_aproponent_of |
pioneering in esports
|
| gptkbp:works_on |
future of esports
|