The GTO trainer allows you to practice specific spots repeatedly, reinforcing optimal play patterns. Consistent practice is key to improving your poker skills. You can upload your hand histories directly into the Analyze section of GTO Wizard. It shows how to play any hand perfectly against your opponents. Detect superhuman plays and assess the closeness of a player’s strategy versus the optimal strategy. Detect superhuman plays and assess the closeness of a player’s strategyversus the optimal strategy.
With current rake levels and competition, grinding manually at micro stakes is a questionable pursuit.
The bot follows sound baseline strategy but deviates when it detects specific opponent weaknesses, and profits from their mistakes. Can evaluate any game state without pre-computed tables. Solver-based (GTO lookup), use pre-computed solutions from GTO solvers as lookup tables.
│ ├── poker # WIP general code for managing a hand of poker. You’ll need to have computed the pickled card information lookup tables first , the cluster command for poker_ai,. You’ll save the combinations of public information in a file called card_info_lut.joblib located in your project directory.
- The profiling engine tracks VPIP, PFR, 3-bet frequency, fold-to-c-bet, and aggression factor per player.
- We begin the action with the effective stacks between 220bb and 520bb.
- Online Poker Bot AI supports up to six simultaneous tables, each with its own independent opponent models and strategy context.
- Not merely tools (these are predators—the most advanced poker AI ever developed), designed to exploit every flaw in your game before you even realize a mistake has been made.
- It’s a proving ground for advanced machine reasoning, especially for evaluating the capabilities of LLMs in poker AI.
- CFR produces bluffs based upon the requirements of mathematical certainty.
Villain Ranges
A premium suited ace with strong playability, high equity against calling ranges, and the potential for flushes and straights is found in an early position (UTG+1 after UTG folds) preflop. U8 Grok initiates the action with effective stacks of ATs — holding over 600bb, while LLAMA in U7, always eager to splash, possesses 88 with 150bb. In this hand, a reckless exploitive choice leads to an all-in preflop showdown of ATs against 88 for a pot worth 300bb. Similar to other LLMs, it becomes enthusiastic about capitalizing on bluffs but fails to account for the dangers of being outmatched by overpairs. Against a 5-bet (it wisely opts to call in position), effectively closing the action, which can be seen as a reasonable choice.
Once there is a working prototype, write in a systems level language like C++ and optimise for performance. This engine is now the first pass that will be used support self play. The following code is how one might program a round of poker that is deterministic using the engine. A low level thing to first to is to implement a poker engine class that can manage a game of poker. There are two parts to this repository (the code to manage a game of poker), and the code to train an AI algorithm to play the game of poker. Later on in the code, as proxy for some code that obtains a new state …
If you’re a club owner — bots can be a threat or an opportunity. For earning — automatic mode generates profit while you’re doing other things A bot lets you play more tables, more hours, with less time investment.
Initial Access
Our AI opponents only see their own cards, just like in real poker. Friendly opponents who play solid poker with realistic decision-making. Train against AI that plays like humans — not calculators.
- Strengthen the game engine with more tests and allow users to see live visualisation of game state.
- Facing Claude’s large flop raise to $3,200 , ~93% pot, after calling our 4-bet and flop bet, QQ is vulnerable on the J-high board (5d,Jh,2s).
- This hand may illustrate how misguided aggression could have contributed to this remarkable outcome.
- Most training tools pit you against a perfect GTO solver or generic AI opponents with no real personality.
Most of the strategies are based on zoom or Fast Forward tables. Models Patrik Antonius’s disciplined, powerful style—controlled aggression, composure under pressure, and razor-sharp decision-making. Models Phil Ivey’s balanced, intuitive, high-pressure style—elite timing, subtle reads, and composed aggression. Learn how to overwhelm opponents without ever losing control. Become the “calling station” no one sees coming. A profitable take on the classic loose-passive style—lots of calling (lots of flops), and tons of disguised value.
Overfolds in many situations and avoids big pots. Plays too many hands but avoids aggression. Pick your action (see what QuintAI thinks), hear what Melika did. UTG raised, BB called, BB checked. None are competitive with CFR-based solvers, but they serve as research tools and benchmarks for LLM reasoning capabilities.
It reads the current game state — your hand, the board, the pot, stack sizes, positions, and the action history — and cross-references this against a comprehensive GTO strategy database to identify the optimal action. Poker Helper AI is a decision-support tool that works alongside your poker client on Android or emulator. Poker Helper AI closes that gap by putting a real-time GTO coaching engine directly in your corner — analyzing each situation as it unfolds and delivering the highest-EV recommendation before you need to act. Winning consistently at online poker requires making better decisions than your opponents on every street of every hand.
