Hal Ashton

18 papers C 1Misc 1Journal 10Unranked 6
YearRankTypeTitle / Venue / Authors
2025 J jnl
Model-Free RL Agents Demonstrate System 1-Like Intentionality.
CoRR
Hal Ashton, Matija Franklin
2024 J jnl
Beyond Preferences in AI Alignment.
CoRR
Tan Zhi-Xuan, Micah Carroll, Matija Franklin, Hal Ashton
2023 J jnl
Concept Extrapolation: A Conceptual Primer.
CoRR
Matija Franklin, Rebecca Gormann, Hal Ashton, Stuart Armstrong
2023 J jnl
Definitions of intent suitable for algorithms.
Artif. Intell. Law
Hal Ashton
2022 — conf
A Method to Check that Participants Really are Imagining Artificial Minds When Ascribing Mental States.
HCI (49)
Hal Ashton, Matija Franklin
2022 C conf
Causal Framework of Artificial Autonomous Agent Responsibility.
AIES
Matija Franklin, Hal Ashton, Edmond Awad, David A. Lagnado
2022 — conf
Defining and Identifying the Legal Culpability of Side Effects using Causal Graphs.
SafeAI@AAAI
Hal Ashton
2022 Misc conf
Missing Mechanisms of Manipulation in the EU AI Act.
FLAIRS
Matija Franklin, Hal Ashton, Rebecca Gormann, Stuart Armstrong
2022 J jnl
Preference Change in Persuasive Robotics.
CoRR
Matija Franklin, Hal Ashton
2022 J jnl
Recognising the importance of preference change: A call for a coordinated multidisciplinary research effort in the age of AI.
CoRR
Matija Franklin, Hal Ashton, Rebecca Gormann, Stuart Armstrong
2022 J jnl
Solutions to preference manipulation in recommender systems require knowledge of meta-preferences.
CoRR
Hal Ashton, Matija Franklin
2022 — conf
The Problem of Behaviour and Preference Manipulation in AI Systems.
SafeAI@AAAI
Hal Ashton, Matija Franklin
2021 — conf
Causal Campbell-Goodhart's Law and Reinforcement Learning.
ICAART (2)
Hal Ashton
2021 J jnl
Definitions of intent suitable for algorithms.
CoRR
Hal Ashton
2021 J jnl
Extending counterfactual accounts of intent to include oblique intent.
CoRR
Hal Ashton
2021 — conf
What criminal and civil law tells us about Safe RL techniques to generate law-abiding behaviour.
SafeAI@AAAI
Hal Ashton
2020 — conf
AI Legal Counsel to train and regulate legally constrained Autonomous systems.
IEEE BigData
Hal Ashton
2020 J jnl
Causal Campbell-Goodhart's law and Reinforcement Learning.
CoRR
Hal Ashton
redb/extractors/decompiler/bninja/opcode_type.py
← Index redb/extractors/decompiler/bninja/opcode_type.py python 
from enum import Enum


class OpcodeType(Enum):
    DATA_MOV = "DATA_MOV"
    STRING_MANIPULATION = "STRING_MANIPULATION"
    LOGICAL = "LOGICAL"
    ARITHMETIC = "ARITHMETIC"
    SYSTEM_CALL = "SYSTEM_CALL"
    FPU_ARITHMETIC = "FPU_ARITHMETIC"
    CPU_FEATURES = "CPU_FEATURES"
    CRYPTOGRAPHIC = "CRYPTOGRAPHIC"
    MISC = "MISC"