Examples
Examples
Try the starting example
- Nodes: name, decision/chance/terminal, terminal payoff or 0
- Root,decision,0 Risky,chance,0 Safe,terminal,30 Win,terminal,100 Lose,terminal,-20
- Branches: parent, child, probability or none for decisions
- Root,Risky,none Root,Safe,none Risky,Win,0.5 Risky,Lose,0.5
- Root node
- Root
- Root expected payoff
- 40
- Preferred child at a root decision
- Risky
- Values by node
- Root: 40; Risky: 40; Safe: 30; Win: 100; Lose: -20
- Decision policy by decision node
- Root: Risky
Try another scenario
- Nodes: name, decision/chance/terminal, terminal payoff or 0
- Root,decision,0 Risky,chance,0 Safe,terminal,30 Win,terminal,100 Lose,terminal,-20
- Branches: parent, child, probability or none for decisions
- Root,Risky,none Root,Safe,none Risky,Win,0.25 Risky,Lose,0.75
- Root node
- Root
- Root expected payoff
- 30
- Preferred child at a root decision
- Safe
- Values by node
- Root: 30; Risky: 10; Safe: 30; Win: 100; Lose: -20
- Decision policy by decision node
- Root: Safe
Calculation method
Calculation method
Root expected payoff
Evaluate terminal payoffs, chance-weighted child values and maximum child values at decisions, recursively.
Preferred child at a root decision
List tied best children at the root if it is a decision.
Values by node
Show each supplied node value in input order.
Decision policy by decision node
Show the maximum-payoff child choice at every reachable decision.
Symbols and units
- a
- Nodes: name, decision/chance/terminal, terminal payoff or 0
- b
- Branches: parent, child, probability or none for decisions
- c
- Root node
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Assumptions & limits
Assumptions & limits
- A finite acyclic decision/chance graph with explicit probabilities and terminal net payoffs. Decisions maximise stated expected payoff; no risk preference or real-world probability is inferred. All nodes must be reachable.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.
Further reading
MIT: engineering decision analysis ↗
Background reading; this does not imply endorsement or independent review of SumFizz.